“Marketing Strategy Meets Wall Street”:
A Research Proposal for MSI-EmoryBI
“The Effect of Brand Acquisition and Disposal on Stock Returns”
Michael Wiles*
Indiana University
Neil A. Morgan
Indiana University
Lopo L. Rego
University of Iowa
*Please address all correspondence concerning this project to:
Michael Wiles
Kelley School of Business
Indiana University
1309 East Tenth Street
Bloomington, IN 47405-1701
Phone: (812) 855-5530
Fax: (812) 855-6440
E-mail: mwiles@indiana.edu
“The Effect of Brand Acquisition and Disposal on Stock Returns”
Abstract
Firms operating in consumer markets generally manage portfolios of brands and make
corporate-level investment decisions regarding additions to and subtractions from their portfolio
through brand acquisition and disposal. While a commonly observed phenomenon, we know
little about the performance effects of firm decisions to acquire or dispose of brands. Here, using
the resource-based view as a theoretical lens and an event study methodology, we examine stock
market reactions to firms’ brand acquisition and disposal announcements in the consumer
packaged goods industry. Initial findings on a sample of 188 brand acquisitions and 128 brand
disposals over the period 1994 through 2006 suggest that firms disposing of brand assets enjoy
abnormal stock returns while firms acquiring brands do not. Drawing on strategic factor market
theory and the diversification literature in strategic management, we identify a number of
boundary conditions under which firms may benefit from acquiring brands and benefit more or
less from disposing of brands.
Introduction
In seeking to better understand the relationship between marketing and firm performance,
a fundamental question is the effect that strategic marketing investments have on shareholder
wealth (Day and Fahey 1988 Rust et al. 2004). A firm’s market value reflects the discounted
value of the firm’s expected future cash flows (e.g., Rappaport 1997). Marketing activities which
affect channels of distribution and consumers in ways which impact the firm’s cash flows
therefore affect shareholder value (e.g., Gruca and Rego 2005). The marketing-finance literature
provides a well-developed theoretical rationale detailing how market-based assets such as brands
can impact firms’ market value by (1) increasing cash flow levels, (2) accelerating cash flows,
(3) decreasing cash flow vulnerability, and (4) increasing the firm’s residual value (Srivastava,
Shervani, and Fahey 1998). These conjectures are supported by a growing body of empirical
evidence (e.g., Barth et al. 1998; Kerin and Sethuraman 1998; Madden, Fehle, and Fournier
2006; Rao, Agarwal, and Dahlhoff 2004) linking brands with competitive advantage for the
firms that own them. As a result, it is increasingly widely accepted that brands are important
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intangible assets that can significantly contribute to firm performance (e.g., Ailawadi, Lehman,
and Neslin 2001; Keller and Lehman 2006; Sullivan 1998).
Most firms operating in consumer markets have a portfolio comprising multiple brands
(e.g., Aaker 2004; Hill, Ettenson, and Tyson 2005). In managing these portfolios firms often buy
or sell brands (e.g., Capron and Hulland 1999; Laforet and Saunders 2005). For example, in 2000
Unilever embarked on a brand portfolio trimming strategy, and by 2003 had sold off several
hundred brands — including well-known brands such as Elizabeth Arden perfumes and Golden
Griddle syrup. Similarly, over the past eight years, Procter & Gamble has disposed of over 1,000
brands. At the same time, other firms have aggressively grown their brand portfolios through
brand acquisitions. For example, following a corporate strategy shift in 2000 ConAgra has built a
portfolio of 48 major brands, only 3 of which were developed in-house. Similarly, Nestle has
purchased a large number of brand assets over the past decade. However, in spite of the active
market in both the acquisition and disposal of brand assets, we have little understanding of this
important phenomenon (Bahadir, Bharadwaj, and Srivastava 2006). In particular, little is known
about whether and how firms benefit from buying and/or selling their brand assets (e.g.,
Varadarajan, DeFanti, and Busch 2006).
We address this significant knowledge gap in this research proposal and provide some
initial empirical insights using a preliminary data set that we have already assembled. More
specifically, we seek to address three questions that are of particular theoretical importance and
managerial interest: (1) do firms enhance their performance by purchasing brands from others?;
(2) if brands are valuable market-based assets, will investors reward or punish firms that dispose
of brand assets?; and (3) can we identify brand, firm, transaction, and strategic factors which
2
significantly affect the returns to buying and selling brands? Figure 1 outlines the broad research
framework we adopt in our initial empirical work addressing these questions.
This research proposal addresses provides new insights in each of the four priority areas
laid out in the MSI-EmoryBI “Marketing Strategy Meets Wall Street” call for proposals. For
example, in terms of priorities #1 and #4 we provide preliminary evidence that investors react to
the disposal of brands and show that stock prices are informed with regard to the acquisition and
disposal of brand assets. We also uncover an interesting asymmetry in how investors appear to
value complementary marketing resources (brands and channel relationships) that requires
further investigation. Relevant to priority #2, we show that the buy-side strategic factor market
for brands is relatively efficient, which provides an important source of information (and initial
support) for brand valuation approaches that projecting cash flows attributable to brands
forwards and discounting them using “multiples” (e.g., Interbrand). In terms of priority #3, we
provide evidence that some of the biggest single marketing investments firms ever make – the
purchase of an existing brand – generally do not produce abnormal stock returns but we also
identify some conditions in which it can.
Theory Framework
The marketing strategy literature linking brand assets with firm performance draws on the
resource based view of the firm (RBV) as its primary theory lens. From this perspective, strong
brands are rare and non-substitutable assets that allow firms to conceive of and execute
inimitable value-creating strategies (e.g., Barney 1991). An important, but often overlooked
foundation of RBV explanations of firm performance is the existence of strategic factor markets
(e.g., Chi 1994; Dierickx and Cool 1989). Strategic factor markets exist whenever firms acquire
the resources required for the implementation of a particular strategy (Makadok and Barney
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2001). The extent to which these strategic factor markets are competitive (efficient) will affect
the likely returns to any strategy that is implemented using acquired resources. This is the result
of competitive markets valuing such resources in ways that reflect the discounted present value
of cash flows that will accrue from implementing the strategy for which they are acquired (e.g.,
Barney 1986; Woolridge and Snow 1990). This is consistent with price systems theory in
classical economics which posits that even when knowledge about the value of a resource in all
potential uses does not exist (as is the case in strategic factor markets), prices which emerge from
a competitive equilibrium will reflect the value of a resource in its best use (Koopmans 1957).
The strategic management literature indicates three key elements that impact the
existence and relative efficiency of strategic factor markets. First, consistent with models of
perfect competition in classical economics, the existence of an efficient market implies multiple
buyers and/or sellers of the strategic factor. This allows bargaining to occur and ensures that the
price mechanism reflects the value of the strategic factor. Second, the availability and
equivalence of information about the value of the strategic factor in use is an important
determinant of strategic factor market efficiency. Perfectly competitive strategic factor markets
require perfect information regarding the strategic factor and its expected value in all possible
alternative uses among and between buyers and sellers. Third, the existence of heterogeneous
resources and capabilities among firms, and the relationship between these idiosyncratic firm
resources and capabilities and the strategic factor under consideration has a significant effect on
strategic factor market efficiency. Strategic factor markets are perfectly competitive when all
buyers and sellers have equivalent resources and capabilities which are equally related to the
productive use of the strategic factor.
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From this perspective, if strategic factor markets are competitive then the full value of the
firm strategies they enable will be reflected in the price paid for the resource(s) and firms will
not be able to obtain abnormal returns from strategies executed using acquired resources. Views
on the existence and efficiency of strategic factor markets vary in the strategic management
literature (Lippman and Rumelt 2003). For example, Barney (1986) maintains that reasonably
competitive (albeit imperfect) markets for strategic resources exist and that a firm can therefore
benefit from strategic resource acquisition only by being better informed about the future value
of strategies requiring the resource in question for their implementation. The more accurate the
expectations of the future value of strategies that can be executed using the resource in question,
the more likely the firm is to avoid overpaying (winners curse) and to be able to spot
undervalued resources (bargains) (Barney 1986). Meanwhile, Denrell, Fang, and Winter (2003)
argue that Barney’s logic may be correct but that most complex resources are so idiosyncratic
that they make accurate valuation difficult, if not impossible, and “imply thin, highly imperfect
markets for strategic resources when indeed there are markets at all.”
Irrespective of these different viewpoints on how efficient strategic factor markets are in
general, RBV theory suggests that firms should only be able to benefit from buying and selling
resources when they can create or exploit imperfections in the relevant strategic factor market
(Barney 1986). Two broad elements in strategic factor market inefficiency that firms may create
and/or exploit have received attention in the theoretical literature: information asymmetry; and,
idiosyncratic asset complementarities. Information asymmetry may exist between a buyer and a
seller and/or among buyers in a strategic factor market with regards to the availability and
accuracy of information regarding the value in use of the strategic factor (e.g., Barney 1986;
1989; Lippman and Rumelt 2003). Asset complementarities involve the idiosyncratic pre-
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existing resources and capabilities of a firm that affect the value in use of a strategic factor,
leading to different valuations between firms for the same strategic factor (e.g., Chi 1994;
Makadok 2001). Barney (1988) describes this in an acquisition context as “when a target is
worth more to one bidder than it is to any other bidders.”
Drawing on these theoretical viewpoints of strategic factor markets suggests that firms
should only benefit from buying and selling brands when the market for brands is (or can be
made) inefficient. Further, strategic factor market theory indicates that (i) information
advantages regarding the accuracy with which buyers and sellers can forecast the value in use of
brands, and (ii) idiosyncratic firm resources and capabilities that are complementary to the brand
and affect the brand’s value in use are likely to be important determinants of whether or not
firms benefit from the acquisition and disposal of brands. Below, we detail how these factors
may be expected to impact the returns to buying and selling brand assets.
Hypotheses
Most of the strategic factor market literature focuses on conditions under which buyers
may be able to generate abnormal returns from acquiring a resource. From this perspective, there
are five factors that may be particularly important in determining the extent to which a firm can
enjoy superior performance as a result of purchasing a brand.
First, information asymmetries between the buyer and the seller and/or between buyers
which affect the accuracy with which the expected value of the brand in use can be forecast
create a factor market inefficiency that can be exploited (Lippman and Rumelt 2003). This is the
“resource-picking” mechanism for creating economic rents where superior knowledge of the
value of the brand allows a firm to purchase the brand for less than its marginal productivity
when used in combination with the firm’s stock of other resources and capabilities (Makadok
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2001). As the brand’s owner, the seller has been able to observe the brand in use in conjunction
with its other resources and capabilities, while prospective brand acquirers have not had this
opportunity. Under most conditions the seller of a brand will therefore have a systematic
information advantage over potential buyers regarding the likely future value of the brand to the
seller. Thus, applying strategic factor market theory to the market for brands suggests that,
absent luck (which is by definition not systematic) a buyer should not be able to succeed in
profiting at all from purchasing a brand (Barney 1986; Denrell, Fang, and Winter 2003).
Second, asymmetries in complementary assets between the buyer and the seller and/or
between buyers can also affect the accuracy with which the expected value of the brand in use
can be forecast, creating a strategic factor market inefficiency (Barney 1986; Conner 1991).
From this perspective, marketing capabilities and channel relationships have been identified as
complementary assets that may that enhance the value in use of brands (e.g., Amit and
Shoemaker 1993). Such complementary assets are nontradeable and are the result of firms’
idiosyncratic investments in different activities over time (Dierickx and Cool 1989; Barney
1989). Complementary assets such as marketing capabilities and channel relationships cannot
therefore simply be acquired by other potential bidders for the brand in question. Makadok
(2001) shows analytically how firm-specific capabilities (such as marketing and brand
management) and resources (such as channel relationships) lead to differential value
expectations from the same acquirable resources among potential acquirers.
Third, diversification research in strategic management suggests that firms benefit from
diversification only when there is a strong marketing or technology link between the businesses
in which the firm is engaged (e.g., Palich, Cardinal, and Miller 2000). Applying this logic to the
acquisition of a brand suggests that the more closely a (non-redundant) brand is related to the
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buying firm’s existing brand portfolio, the more the buying firm should benefit from acquiring
the brand. The economic logic for this expectation concerns the existence of synergies between
closely-related brands that are not available to unrelated brands and is closely allied to the above
arguments concerning complementary assets (e.g., Barney 1988). For example, purchasing a
brand in a category that is similar to that of the firm’s existing brands can enable the acquired
brand to be sold through the firm’s existing distribution channel producing synergistic savings
that will not be available if the firm purchased a brand in an unrelated category.
Finally, an important element in efficient markets is a large number of buyers and sellers.
As brands are idiosyncratic assets (a characteristic that adds to their value for consumers and
therefore for their owners), we would not expect there to be many occasions in which there may
be qualitatively similar brands for sale from multiple sellers in a strategic factor market. From a
buyer’s perspective, however, the greatest danger lies in the existence of multiple interested
buyers for a single brand asset, since limited supply and many buyers will lead to competition
that will likely bid up the value of the brand to a level that is equivalent of its highest expected
value in use. At which point, it becomes impossible for any firm to obtain positive returns form
purchasing the brand. Thus when there is an “auction”, i.e. multiple potential buyers are
approached to gauge their interest in purchasing the brand, we would expect the ultimate buyer
to be less able to enjoy superior performance as a result of the purchase.
More formally, the above arguments suggest that:
H1: Brand acquisitions are not associated with firms’ abnormal stock returns
H2: Brand acquisitions will be more positively (negatively) associated with firms’ abnormal
stock returns when:
(a) the acquired brands provide new distribution resources to the firm
(b) the buying firm has superior (inferior) brand-related marketing resources and
capabilities
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(c) the acquired brands are more closely (distantly) related to the firm’s existing business(es)
(d) there are a smaller (larger) number of potential buyers
Resource sellers have not been the subject of as much attention as buyers in the strategic
factor market literature. However, drawing on strategic factor market theory we suggest that
there are four factors that may be important in determining the extent to which a firm can enjoy
superior returns from disposing of a brand.
First, as outlined above in the context of buying brands, information asymmetries
between the buyer and the seller which affect the accuracy with which the expected value of the
brand in use can be forecast creates a factor market inefficiency that can be exploited (Lippman
and Rumelt 2003). The “resource-picking” mechanism for creating economic rents suggests that
such information asymmetries can be valuable in enabling the firm to know what assets not to
invest in as well as those assets that should be acquired (Makadok 2001). The selling firm should
have an information advantage relative to any purchaser concerning detailed non-public
knowledge of the brand and its performance prospects (e.g., Denrell, Fang, and Winter 2003).
Perhaps more importantly, with complete information regarding the brand asset in use in
combination with the firm’s existing stock of other resources and capabilities, the selling firm is
able to more accurately assess the value of owning the brand than any firms who may consider
purchasing the brand (Makadok and Barney 2001). Thus, sellers of brand assets should
systematically have an information advantage relative to buyers. Buyers may sometime be lucky
but this is not systematic (Barney 1986).
Second, armed with this information advantage, if a firm is willing to sell a brand at a
given price then the brand must have a more valuable alternative “next best use” (Peteraf 1993).
That is, managers in the selling firm must believe that another firm (the buying firm) has
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superior brand-related resources and capabilities such that the buyer will pay a market price for
the brand and not lower their returns by doing so (cf. Barney 1986). By selling the brand,
managers in the selling firm also signal to investors that the resources freed up by disposal of the
brand in question will deliver a greater return if they are deployed on other projects, activities,
brands, etc. (e.g., Carlotti, Coe and Perry 2004; Varadarajan, DeFanti, and Busch 2006). For
example, a firm may dispose of a brand because it believes that the returns from paying down its
debt are greater than those of owning the brand – the reason Levi’s announced for selling its
Dockers brand.
Third, the brand portfolio literature suggests that reducing the size of a brand portfolio
may result in efficiencies that lower costs (e.g., Knudsen et al. 1997; Laforet and Saunders
1999). For example, following its portfolio slimming strategy announcement in 2000 and the
selling off of more than 100 businesses and several hundred brands in the following three years,
procurement standardization and improved product mix led Unilever to improve its operating
margins from 11.2 percent to close to 15 percent (Pierce and Moukanas 2002). Thus any sale of
brand assets may increase the efficiency with which the firm may manage its remaining brand
portfolio.
Finally, the diversification literature in strategic management suggests that firms that
dispose of brands which are unrelated to their core business should enjoy stronger positive
abnormal returns. The intuition is that brands that are unrelated to the firm’s core resources and
capabilities are unlikely to enjoy any significant synergistic economic benefits (a “parenting
advantage”) from being owned by the firm (e.g., Campbell, Goold, and Alexander 1995). There
is therefore likely to be both a higher value in use for the brand in the portfolio of another firm
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which should lead to a higher market price being paid for the brand, and also to be higher returns
available for the funds generated from selling the brand by investing in other brands.
More formally, the above suggests that:
H3: Brand disposals are associated with firms’ abnormal stock returns
H4: Brand disposals will be more (less) positively associated with firms’ abnormal stock
returns when:
(a) the selling firm has inferior (superior) brand-related resources and capabilities
(b) the selling firm signals (does not signal) that it has identified higher return investments
for the funds generated by the disposal of the brand
(c) the brand(s) sold significantly reduce the size of the selling firm’s brand portfolio
(d) the brand(s) sold are more distantly (closely) related to the firm’s existing business(es)
Research Method
We use the event study methodology to assess the impact of unexpected information on
the firm’s stock price. Finance theory asserts that a stock price reflects all public information
about the firm, so only unexpected information can change the price of a stock (Fama et al.
1969). Thus, if the new information causes investors to expect that the firm will garner lower
(higher) future cash flows, then the firm’s stock price drops (rises) in reaction to the new
information. The stock’s abnormal return, the difference between the stock’s actual return and its
expected return based on general market movement, is a measure of the event’s effect on the
firm’s market value. We follow the standard protocols for the short-term event study method,
and excellent summaries of this method currently exist in the literature (e.g., Srinivasan and
Bharadwaj 2004). When events are confined to a single industry, cross-sectional dependence in
the returns biases the standard deviation estimate downward (MacKinlay 1997), inflating the
associated test statistics. We correct for this bias using the Jaffe (1974) portfolio method.
Sample
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We selected the companies included in the American Customer Satisfaction Index
(ACSI) as our sampling frame for three reasons. First, the ACSI is designed to be representative
of the consumer sector of the US economy, and includes the largest firms in each of 40 different
industries (representing 70% or more of the sales in these industries and collectively representing
more than 42% of US GDP), which should minimize generalizability concerns (see Fornell et al.
1996). Second, since consumer spending represents more than 70% of US GDP and brands
occupy a more central role in the business models of consumer as opposed to business-tobusiness focused companies, a sample of large consumer companies is more appropriate for the
topic of our study. Third, most of the firms in the ACSI are publicly-traded which is required for
us to be able to assess stock returns as required in an event study. We focused in our initial data
collection efforts on seven of the largest industries in the ACSI: Apparel; Athletic Shoes and
Sportswear; Beverages; Cigarettes; Beer; Food/Pet Food; and, Personal Care. Eliminating private
companies resulted in an initial sample of 29 firms (see Appendix 1)1. Our sample includes all
brand acquisitions and disposals for these firms from Jan 1, 1994 through December 31, 2006.
Our disposal event is the announcement of a sale or a pending sale of a brand, identified
through a Factiva search of company news releases and press reports. Our acquisition event is
the announcement that an agreement has been reached to acquire a brand. When earlier press
reports mentioned that the firm was negotiating to purchase the brand, the announcement that the
firm was negotiating to purchase the brand was considered to be the event. We compiled our list
of brands that were acquired and disposed through four sources. First, we searched the SDC
Platinum database to construct an initial list of the acquisitions and disposals for each firm.
1
Our sample size is comparable with many other event studies. For example, Aaker and Jacobson (1994) and Lane
and Jacobson (1995) each had a sample of 34 firms, with a much smaller number of events over a shorter time
period than in our data set and Agrawal and Kamakura (1995) had a sample of 35 firms and 110 events over a
similar time period.
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Second, we read the firms’ annual reports over the sample period to identify additional brand
acquisitions and disposals. Third, we examined all of the firms’ press releases and investor
relations material posted on their websites. Finally, we also conducted a Factiva search for brand
acquisitions and disposals, centering our search on those terms. Brand disposals mandated by
government regulators following an acquisition were not included in our sample.
Overall, we found 394 brand acquisitions and 270 brand disposals. After removing brand
acquisitions and disposals in non-G7 countries (e.g., Poland, Argentina, Turkey) and those
involving brands focused on the non-consumer foodservice channel, we were left with 238 brand
acquisitions and 199 brand disposals. Events where we found contaminating information
pertaining to earnings announcements, stock splits, key executive changes, unexpected stock
buybacks, or changes in the dividend within the two trading day window surrounding the release
of the letter were removed from the sample. Sixty-eight events had to be eliminated due to the
presence of confounding information. An additional 53 events had to be dropped due to limited
data availability about the event (e.g., we could not locate a four digit SIC code for the brand or
we were unable to determine the brand’s yearly revenues), leaving 188 announcements of brand
acquisitions and 128 announcements of brand disposals2.
Variable Operationalization
Dependent variable. Abnormal stock returns were obtained using the Eventus® software
program on WRDS. An abnormal stock return is computed as detailed above.
Independent and control variables. These were operationalized using both information
coded from the announcements we collected and also from secondary databases such as
2
In only 17 observations were the purchase and disposal events matched in our two databases suggesting that the 29
large companies in our sample rarely swap brand assets. In only 10 of these matched pairs did we find no
confounding information and include these in our analyses.
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COMPUSTAT. Details of the variable operationalization are contained in Appendix 2. A content
analysis of the announcements was conducted. A coder recorded the data in the announcements
using a standardized coding scheme. We plan to use a second coder for all events to allow an
assessment of inter-coder agreement that will provide additional confidence in the quality of
coded data (see future research plans). Descriptive statistics for all variables are reported in
Table 1 and correlations among the variables in the brand acquisition and disposal samples are
reported in Tables 2 and 3 respectively.
[Insert Tables 1, 2 & 3 Here]
PRELIMINARY ANALYSES AND RESULTS
Event Study Analysis and Results
Daily stock returns were gathered from the University of Chicago’s Center for Research
in Security Prices (CRSP), and parameters of the market model were estimated over a 90 trading
day estimation window, ending 6 days prior to the event. The daily and cumulative average
abnormal returns for windows surrounding the event date are presented in Table 4. All statistical
tests are two-tailed. To allow for uncertainty over when the information was available to
investors, common event study practice is to determine the event window empirically (Agrawal
and Kamakura 1995; Brown and Warner 1985). For the disposals, results are strongest for the
event day, but for the acquisitions we observe no significant abnormal return on any of the days
surrounding the event. We find no evidence that information leaks to the market before the
announcement of the acquisition or sale of the brand. Motivated by the strength of the results for
the (0,0) window for the disposals, as well as the idea that investors should react swiftly to these
material firm events, we focus our analysis on the (0,0) window.
(Insert Table 4 here)
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Supporting H1, we find that the announcement of brand acquisitions is not associated
with a significant stock price move, with an abnormal return of -.18 on average during the [0,0]
window, supporting H1 (tJaffe portfolio test = -0.53, p > .10), and confirming that investors neither
reward nor punish firms for buying brand assets. On the event date, 89 of the 188 abnormal
returns were positive (tgeneralized sign test = -0.26; p > .10). Further, the Wilcoxon signed rank test, a
more powerful nonparametric test incorporating the sign and magnitude of the abnormal returns,
was also insignificant (ZWilcoxon = -542.00, p > .10), suggesting outliers did not overly influence
our insignificant results (McWilliams and Siegel 1997)3.
In contrast, we find that the announcement of brand disposals is associated with a
significant stock price increase of .49% on average during the [0,0] window, supporting H3 (tJaffe
portfolio test =
2.80, p < .01), with 78 of the 128 abnormal returns being positive (tgeneralized sign test =
2.65, p < .01). Further, the Wilcoxon signed rank test was also significant (ZWilcoxon = -1056.00, p
< .01), suggesting outliers did not overly influence our results (McWilliams and Siegel 1997).
The disposal announcement was associated with an average gain of $141 million dollars in
shareholder value.
Cross-sectional Regression Results
We tested H2 and H4 regarding the impact of different firm, transaction, brand, and
strategic characteristics on the abnormal stock returns to the acquisition and disposal of brand
assets through a regression of the [0,0] cumulative abnormal return on the independent variables
and the controls. The cross-sectional results are presented in Tables 5 and 6.
[Insert Tables 5 and 6 here]
3
Sensitivity analysis indicated that the negative abnormal return is robust with respect to other market model benchmarks and
statistical tests. The significance of [0,0] abnormal return is unaffected by using a value-weighted market portfolio. Results for
the [0,0] window are also significant using Brown and Warner’s (1980) crude dependence adjustment test statistic.
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Brand Acquisitions
Table 5 reveals that our cross-sectional regression has significant explanatory power
(Adjusted R2 of .17). Among the control variables, we find that the abnormal returns to acquiring
a brand are positively associated with purchases of Canadian (p<.10) and French (p<.05) brands,
and negatively associated with the relative size of the acquisition (p<.001). Surprisingly, neither
announcements concerning the expected effect of the brand acquisition on the firm’s earnings or
analyst perceptions of the relative price paid for the brand had a significant relationship with
abnormal stock returns.
In terms of H2, we find support for H2(a) with a positive coefficient (p<.05) when the
acquired brand brings new distribution resources to the acquirer firm. We also find some support
for H2(b), with a marginally significant (p<.10) positive coefficient on the Tobin’s Q variable
(our proxy for a firm’s marketing capabilities). With a non significant coefficient for the unrelatedness and auction variables we find no support for either H2(c) or H2(d). Beyond the
hypothesis tests we also included an interaction of Tobin’s Q and whether or not the brand was
being purchased at auction. As seen in Table 4, we found a significant negative interaction
between these two variables in predicting abnormal stock returns to brand acquisitions.
Brand Disposals
Table 6 reveals that our cross-sectional regression of the abnormal returns to brand
disposals has good explanatory power (Adjusted R2 of .32). Among the control variables we find
stronger positive returns to disposals of brands that are primarily geographically strong in France
(at the p<.10 level). We also find that announcements concerning an expected positive effect of
the disposal on the selling firm’s earnings (p<.05) and analyst perceptions of the price realized in
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selling the brand (p<.05) were both positively associated with abnormal stock returns to brand
disposals.
In terms of H3, we find mixed support for H3(a) with an insignificant coefficient on the
Tobin’s Q variable (our proxy for a firm’s marketing capabilities) but a strong positive
coefficient on the sale of brands for which the selling firm has inferior distribution resources
(p<.01). We find no support for H3(b). In fact we observe that when the selling firm identifies
higher return uses for the cash released in disposing of the brand, this is either not significantly
associated with abnormal stock returns, or in the case of investing in more profitable brands
(p<.10) and reducing debt (p<.10), investors tend to react negatively rather than positively. We
find some support for H3(c), since the sale of relatively larger brands (implying a larger
opportunity for efficiency savings through the reduction in the selling firm’s brand portfolio) is
positively associated with greater abnormal stock returns (p<.001). With a marginally significant
positive coefficient (p<.10) for the un-relatedness variable we also find some support for H3(d).
DISCUSSION AND IMPLICATIONS
Our study reveals no significant abnormal returns associated with the acquisition of brand
assets. This does not suggest that brand assets are not valuable. Rather, in line with strategic
factor market theory, our results indicate that the buy-side market for brand assets is relatively
efficient in valuing brands. This contrasts with the “winners curse” phenomenon noted in the
acquisitions literature in strategic management and economics which shows that acquirers
consistently pay too high a premium when purchasing other firms (e.g., Varaiya 1988). Thus, our
results suggest that acquirer expectations of the future returns from the purchase of a single asset
(a brand) are more accurate than when purchasing a collection of different types of assets (an
entire firm). The relative efficiency of the buy-side factor market for brands provides some
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support for valuation mechanisms such as those used by Interbrand that use the prices paid for
brand assets in recent market transactions in a particular sector as an important determinant of
the “multiple” used to compute the value of specific brands.
However, the results of our test of H2(d) indicate that it is not the presence of multiple
prospective bidders for a brand that drives the insignificant returns from brand purchase (and by
inference the efficiency of the strategic factor market for brands). We further explored this result
by examining whether or not this finding is moderated by an interaction with the firm’s
marketing capabilities (Tobin’s Q). The significant negative interaction suggests that brand
acquirers with lower marketing capabilities may be better rewarded in an auction situation than
those with higher capabilities. One possible explanation is that this result may be driven by firms
acquiring brand management teams as well as the brand(s) on which they work and being
rewarded by investors as a result – a possibility we will explore as we further develop our
database and analyses.
The cross sectional regression results provide some support for suggestions that when
buying brands, acquirers with stronger marketing capabilities (those with higher Tobin’s Q’s
scores) may be rewarded (or less punished) when they purchase brand assets. This result is in
contrast to Bahadir, Bharadwaj, and Srivastava (2006) who find acquirer marketing capabilities
do not affect the value placed on brands in the context of whole company acquisitions. The
regression results also indicate that when buying brands, acquirers that have the ability to use the
purchased brand’s channel relationships to expand the distribution of their existing brand
portfolio are rewarded when they purchase brand assets. However, this is not true of using the
acquirer’s existing channel relationships to expand distribution of the purchased brand. A
subsequent split group analysis revealed that brand acquisitions which bring new distribution
18
relationships to the acquirer produce a .96% positive abnormal return on average during the [0,0]
window (tJaffe portfolio test = 4.04, p <.01) with 13 of 14 abnormal returns being positive (tgeneralized sign
test =
3.35, p < .01). In contrast, brand acquisitions designed to leverage the acquirer’s existing
channel relationships produce a -.55% abnormal return on average during the [0,0] window (tJaffe
portfolio test =
-0.46, p >.10) with 10 of 18 abnormal returns being positive (tgeneralized sign test = .56, p
>.10).
This suggests an interesting asymmetry – leveraging the acquirer’s existing brands
through new channels is rewarded while leveraging newly acquired brand(s) through the
acquirer’s existing channels is not. Theoretically, this suggests that the channel relationships
associated with a brand may be undervalued by firms in strategic factor markets. It also suggests
that investors believe that firms have the opportunity to further leverage their brand assets into
new channels. It is also possible that it is the relative size of the two opportunities that drives
these results. The average size of the acquired brands in our sample is around 5% of the
acquirer’s total sales revenue, so it is possible that the absolute returns of leveraging the
acquirer’s larger brand portfolio into a new channel are greater than those possible from selling
the newly acquired brand(s) through the firm’s existing distribution network. This possibility
will be investigated in our future analyses.
While the regression results indicate that the degree of diversification implied in the
purchase of the brand (un-relatedness) does not drive abnormal returns, this is a very coarse
grained variable which does not allow us to compare our findings with those of the
diversification literature in strategic management. We therefore did some post-hoc analyses with
a finer grained set of variables where we coded each brand in terms of whether it was in the same
19
industry and market segment, in the same industry in an adjacent market segment, or in an
unrelated industry. Split group analysis of the acquisition sample indicate that investors are
unmoved by purchases within the same market segment with a -.07% on average during the [0,0]
window (tJaffe portfolio test = -.44, p >.10) with 20 of 42 abnormal returns being positive (tgeneralized sign
test =
-.00, p > .10). This may indicate that investors see any relatedness (synergy) benefits from
acquiring brands in the same market segment as being offset by overlap or “redundancy”
between the acquired brand and the brands that are already in the acquirer’s portfolio which can
reduce price premiums and weaken manufacturing and distribution economies (e.g., Pierce and
Moukanas 2002; Varadarajan, DeFanti, and Busch 2006).
We also found that consistent with the diversification literature in strategic management
investors reward purchases in an adjacent market segment to the firm’s existing business, and
tend towards punishing acquisitions in unrelated industries. Our split group analysis of the
acquisition sample indicate that brand acquisitions in adjacent market segments produce a .58%
positive abnormal return on average during the [0,0] window (tJaffe portfolio test = 2.33, p <.05) with
22 of 34 abnormal returns being positive (tgeneralized sign test = 1.81, p < .10). In contrast, brand
acquisitions in unrelated industries produce a -.45% abnormal return on average during the [0,0]
window (tJaffe portfolio test = -1.42, p >.10) with 47 of 112 abnormal returns being positive (tgeneralized
sign test =
-1.33, p >.10).
On the sell-side our results reveal a significant, positive abnormal return associated with
the sale of brand assets, indicating that firms are rewarded when investors become aware of a
pending sale of brand assets. This is consistent with strategic factor market theory regarding
information asymmetry and our conjecture that because sellers have more knowledge and
information regarding the brand they have more accurate expectations about the brand’s value in
20
use. Theoretically, this is a strategic factor market imperfection which seller firms can exploit
and our results suggest that investors are aware of this benefit to sellers of brands.
The positive abnormal returns to the sale of a brand are even more positive when selling:
non-core business brands; larger brands; and brands that are primarily French. The enhanced
positive returns when selling a non-core business brand is consistent with Varadarajan, DeFanti,
and Busch’s (2006) conjecture that firms will do so if the brands are likely to fetch a premium in
the marketplace. The enhanced positive returns from selling larger brands mirrors the negative
returns from buying bigger brands in the acquisition sample. Brand disposals that contribute
positively to earnings and those that realize a higher price than analysts may have expected are
also associated with abnormal positive returns in our analyses which is consistent with a
“shareholder value maximization” perspective on investor behavior (Woolridge and Snow 1990).
There are two other interesting results revealed in our regression analyses of the positive
abnormal returns to selling brands. First, we find that selling brands for which the selling firm
had limited distribution resources relative to other firms is positively related to abnormal returns.
In RBV terms this is suggestive of a “better use” available in a strategic factor market for the
brand asset and an absence of a “parenting advantage” for the seller (e.g., Peteraf 1993;
Campbell, Goold, and Alexander 1995). For a tradable asset such as a brand, this should result in
the expected value of ownership of the brand being higher to another firm with superior
distribution resources, resulting in a higher valuation for the brand (Barney 1986; 1989). Perhaps
most interesting here is that this result is not mirrored in the brand acquisition findings.
Second, we find that announcements detailing the strategic logic of the disposal (i.e. the
use to which the proceeds of the sale will be put) do not enhance the positive abnormal returns
and in the case of announcements of investing in more profitable brands and reducing debt, the
21
effect may even be negative. Our speculation for this result is that investors may view paying
down debt or investing in more profitable (but not necessarily faster growing) brands as an
indicator that the firm’s managers do not see significant growth opportunities that may provide
better returns.
LIMITATIONS
One caveat of the event study methodology is that it does not identify the mechanism for
explaining why any abnormal return occurs (Johnson and Tellis 2007). We assumed that
investors’ response would be predicated by the variables thus far examined, but surveys of
investors will be useful to confirm this assumption.
Further, we need to more systematically examine the purchase process when the acquirer
firm competes in an auction. There are a number of stages in this process: (1) firms are rumored
to bid, (2) firms bid, (3) one firm becomes a front-runner, (4) a firm enters into talks, and (5) an
agreement is reached. Currently we have used stage #4 as our event, but results may change if a
different stage is used. Further, if #2 is used, this could expand our sample by including more
firms that bid but did not buy.
22
Appendix 1
Companies and Industries Included in Complete Case Analysis Data Set
COMPANIES
Anheuser-Busch
Cadbury Schweppes
Campbell’s Soup
Clorox
Coca-Cola
Colgate-Palmolive
ConAgra Foods
Dial
Del Monte
Dole Food
General Mills
HJ Heinz
Hershey
Jones Apparel
Kellogg’s
Kraft Foods
Liz Claiborne
Molson Coors
Nike
Pepsi Co
Reebok
Reynolds American
Reebok
Reynolds American
Sara Lee
Quaker Oats
Tyson Foods
Unilever
VF Corporation
INDUSTRIES
Apparel
Athletic Shoes
Beverages - Beer
Beverages - Soft drinks
Food Processing
Tobacco - Cigarettes
Personal Care Products
26
Appendix 2
Operationalization of Independent and Control Variables
Type of
Variable
Brand-Level
Factors
Firm-Level
Factors
Transaction
Factors
Distribution
Factors
Strategic
Logic
Variable
Operationalization
Un-relatedness
If the 4 digit SIC code for the acquirer and target in the transaction
provided by SDC Platinum differed in their first 2 digits
Relative size
Geographic presence
of the brand
Disposed brand has
inferior distribution
resources (D)
Tobin’s Q
Prior year sales of the brand / prior year sales of the firm
The main countries within the G7 that the brand operated in were
coded from press reports of the transaction
Whether the firm decided to sell because the brand’s distribution
resources were inferior to its competitors, as coded from press
reports of the transaction
Calculated following Chung and Pruitt (1994) and Srinivasan
(2006)
Market Value
Stated earnings
impact
Closing price X shares outstanding from CRSP
Whether the acquisition/disposal would have an accretive (1),
dilutive (-1), or no impact (0) on earnings, coded from press
reports of the transaction
Whether price was deemed high (1) or low (0) by market
observers, coded from press reports.
Coded using the terms “auction”, “bid”, and “bidders”, coded
from press reports.
When the brand was acquired in part to allow the firm to sell in
new channels or geographies, as coded from press reports (i.e.,
Campbell Soup buying France’s Liebig).
Perception of brand’s
price
Brand was purchased
in an auction (A)
Acquired brand
provides new-to-thefirm distribution
resources (A)
Target bought to
leverage acquirer’s
distribution resources
(A)
To focus on faster
growing brands (D)
To focus on more
profitable brands (D)
To focus on core
brands (D)
To reduce debt (D)
To buy back shares
(D)
When the acquiring firm stated that a reason for the acquisition
was to be able to expand the brand’s sales by leveraging the firm’s
distribution strengths (e.g., P&G’s purchase of Tambrands)
If firm identified this as a rationale for the disposition, as coded
from press reports.
If firm identified this as a rationale for the disposition, as coded
from press reports.
If firm identified this as a rationale for the disposition, as coded
from press reports.
If firm identified this as a rationale for the disposition, as coded
from press reports.
If firm identified this as a rationale for the disposition, as coded
from press reports.
27
Figure 1
Outline Research Model
•
Brand-Level
Factors
•
•
•
Outside of the firm’s major industry
(2-digit SIC)
Relative size (brand sales/firm sales)
Disposed brand has inferior distribution
resourcesD
Geographic presence of brand (U.S.,
Canada, U.K., France, Germany, Italy)
Firm-Level
Factors
•
•
Tobin’s Q
Market value
Transaction
Factors
•
•
•
•
Brand purchased in an auctionA
Auction X Tobin’s Q interactionA
Stated earnings impact
Perception of brand’s price
•
Acquired brand provides new-to-the-firm
distribution resourcesA
Target bought to leverage acquirer’s
distribution resourcesA
Distribution
Factors
Strategic
Logic
•
•
•
•
•
•
To focus on faster growing brandsD
To focus on more profitable brandsD
To focus on core brandsD
To reduce debtD
To buy back sharesD
Abnormal
Return for
Brand
Acquisition /
Disposal
A – applies only to brand acquisitions
D – applies only to brand to disposals
Control variables
28
Table 1
Descriptive Statistics
Acquisition Sample
Variable
(0,0) Abnormal return (in percent)
Un-relatedness (outside of the firm’s major 2 digit SIC industry)
Relative size of acquisition (acquired brand’s sales / acquirer’s sales)
Acquirer bought entire firm
Geographic presence: USA
Brand-Level
Geographic presence: Canada
Factors
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
Tobin’s Q
Firm-Level
Factors
Market value (in billions $)
Acquisition has accretive/dilutive earnings impact
Transaction
Perception of price paid (high price: 1, low price: -1)
Factors
Brand was purchased in an auction
Acquired brand provides new distribution resources to the firm
Distribution
Factors
Target bought to leverage acquirer’s distribution resources
Mean
Std.
Dev.
Max.
Min.
-.18
.22
.05
.60
.76
.08
.12
.11
.06
.05
2.22
28.50
.10
.08
.13
.07
.10
2.52
.41
.16
.49
.43
.27
.33
.31
.25
.23
1.23
39.86
.48
.33
.34
.26
.30
-11.39
.00
.00
.00
.00
.00
.00
.00
.00
.00
.43
.14
-1.00
-1.00
.00
.00
.00
15.87
1.00
1.92
1.00
1.00
1.00
1.00
1.00
1.00
1.00
9.91
192.91
1.00
1.00
1.00
1.00
1.00
Disposal Sample
Variable
Mean
(0,0) Abnormal return (in percent)
Un-relatedness (outside of the firm’s major 2 digit SIC industry)
Disposed brand’s percent of prior year firm sales
Disposed brand has inferior distribution resources
Geographic presence: USA
Brand-Level
Geographic presence: Canada
Factors
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
Tobin’s Q
Firm-Level
Factors
Market value (in billions $)
Disposal has accretive/dilutive earnings impact
Transaction
Factors
Perception of price received (good: 1, poor: -1)
To focus on faster growing brands
To focus on more profitable brands
Strategic
To focus on core brands
Logic
To reduce debt
To buyback shares
29
.49
.34
.02
.05
.65
.22
.17
.13
.14
.13
2.32
28.24
-.02
-.01
.33
.15
.67
.08
.02
Std.
Dev.
1.83
.47
.04
.21
.48
.42
.38
.34
.35
.34
.93
36.50
.31
.20
.47
.36
.47
.27
.15
Min.
Max.
-3.01
.00
.00
.00
.00
.00
.00
.00
.00
.00
.89
.07
-1.00
-1.00
.00
.00
.00
.00
.00
10.86
1.00
.31
1.00
1.00
1.00
1.00
1.00
1.00
1.00
5.51
141.38
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Table 2
Correlations of Variables in the Acquisition Sample
Variable
(0,0) Abnormal return (in percent)
Outside of the firm’s major industry (2 digit SIC)
Relative size (acquired brand’s sales / acquirer’s sales)
Acquirer bought entire firm
Geographic presence: USA
Brand-Level
Geographic presence: Canada
Factors
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
Tobin’s Q
Firm-Level
Factors
Market value (in billions $)
Acquisition has accretive/dilutive earnings impact
Transaction
Perception of price paid (high price: 1, low price: -1)
Factors
Brand was purchased in an auction
Acquired brand provides new distribution resources to the firm
Distribution
Factors
Target bought to leverage acquirer’s distribution resources
Correlations
1.00
.10
-.38
-.02
-.07
.09
.06
.24
.21
.23
.04
.02
.16
-.14
-.00
.13
-.05
1.00
-.08
.17
.08
.03
-.04
-.10
-.03
-.01
-.11
.02
.00
-.01
-.02
-.05
.05
1.00
.03
.08
.15
.08
-.04
-.01
-01
-.06
-.09
-.03
.14
.33
-.02
-.02
Note: correlations with an absolute value ≥ .14 have a p-value < .05.
30
1.00
.28
-.04
-.26
-.18
-.05
-.05
.03
-.04
.03
-.00
-.06
.07
.23
1.00
-.16
-.55
-.57
-.41
.37
-.05
-.05
.01
.06
.11
.06
.14
1.00
.13
.03
.08
.11
-.02
-.07
-.02
.17
.17
-.08
-.03
1.00
.24
.23
.20
.06
.03
.13
.01
.14
-.04
-.07
1.00
.47
.53
.10
.13
.04
-.03
-.08
.03
-.11
1.00
.52
-.03
.05
.08
.00
-.04
-.07
-.08
1.00
-.06
.04
.05
.01
-.02
-.07
.00
1.00
.64
-.14
.09
-.01
-.07
.14
1.00
-.17
.11
-.02
-.14
.14
1.00
-.29
-.01
.16
-.10
1.00
.24
-.07
-.02
1.00
.07
.-.07
1.00
-.09
1.00
Table 3
Correlations of Variables in the Disposal Sample
Variable
(0,0) Abnormal return (in percent)
Outside of the firm’s major industry (2 digit SIC)
Disposed brand’s percent of prior year firm sales
Brand-Level
Factors
Disposed brand has inferior distribution resources
Geographic presence: USA
Geographic presence: Canada
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
Tobin’s Q
Firm-Level
Factors
Market value (in billions $)
Disposal has accretive/dilutive earnings impact
Transaction
Factors
Perception of price received (good: 1, poor: -1)
To focus on faster growing brands
Strategic
Logic
To focus on more profitable brands
To focus on core brands
To reduce debt
To buyback shares
Correlations
1.00
.13
.41
.36
-.08
-.05
.05
.15
.22
.05
-.03
.01
.01
.18
.16
-.08
.15
-.04
.05
1.00
.01
.08
.14
.10
-.06
.01
.05
.06
.06
.15
.09
-.14
.03
-.02
.07
.04
-.00
1.00
.02
.06
-.05
.10
.12
.12
.04
-.15
-.15
-.15
-.03
.12
.05
-.01
.23
.09
1.00
.01
.06
-.00
-.09
.12
.02
-.09
-.03
-.11
.20
.08
.01
.08
.07
-.03
Note: correlations with an absolute value ≥ .18 have a p-value < .05.
31
1.00
.19
-.49
-.39
-.41
-.39
-.03
.17
.02
-.11
-.04
.08
-.13
.03
-.10
1.00
-.04
-.04
.00
.02
-.02
-.16
.09
.12
.15
.15
-.07
-.01
-.08
1.00
.31
.35
.43
-.06
-.15
.02
.12
.03
.04
.05
.02
.07
1.00
.44
..39
.06
.00
.02
.02
.07
.03
.18
.14
.09
1.00
.37
.07
-.14
.02
.13
.05
-.11
.14
.05
-.06
1.00
-.01
-.01
.17
.13
.07
.03
.08
-.03
-.06
1.00
.41
.08
-.01
.05
.01
.10
-.20
-.10
1.00
.03
-.06
-.15
.07
.09
-.08
.09
1.00
-.13
-.07
.02
.07
-.18
.01
1.00
.20
-.09
.06
.16
.01
1.00
-.01
.17
-.08
.00
1.00
.06
-.12
.08
1.00
-.11
-.11
1.00
.34
1.00
Table 4
Abnormal Returns and Test Statistics for Windows Surrounding the Event Day
Acquisition Sample
Event Window
-1, 0
0, 0
0, 1
Abnormal
Return (%)
-.06
-.18
-.23
Jaffe (1974)
Portfolio tstatistic
-.40
-.53
-.73
# Positive
(Total)
96 of 188
89 of 188
96 of 188
Generalized
Sign test
.76
-.26
.76
Wilcoxon
Signed Rank
test
145.00
-542.00
-529.00
Disposal Sample
Event Window
-1, 0
0, 0
0, 1
Abnormal
Return (%)
.58
.49
.50
Jaffe (1974)
Portfolio tstatistic
2.51**
2.80***
2.47**
32
# Positive
(Total)
Generalized
Sign test
71 of 128
78 of 128
69 of 128
1.41
2.65***
1.06
Wilcoxon
Signed Rank
test
940.00**
1056.00**
691.00
Table 5
Cross-Sectional Regression Results on the Standardized Abnormal Return for the Event
Day for the Brand Acquisitions (0,0) [In Percent]
Brand-Level, Firm-Level,
Transaction, and
Distribution-Level Factors
Parameter
Estimate
t-value
-.65
-1.40
Independent Variable
Intercept
Brand-Level Factors
Un-relatedness (brand is outside of the firm’s major industry)
Relative size of acquisition (acquired brand’s sales / acquirer’s sales)
Acquirer bought entire firm
Geographic presence: USA
Geographic presence: Canada
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
.29
-6.14***
-.26
.41
.74*
-.24
1.13**
.75
.15
.96
-4.68
-1.10
1.06
1.71
-.59
2.42
1.59
.26
Firm-Level Factors
Tobin’s q
Market value
.20*
-.00
1.67
-1.37
Transaction Factors
Acquisition expected to have an accretive/dilutive earnings impact
Perception of price paid (high price: 1, low price: -1)
Brand was purchased in an auction
Auction X Tobin’s Q interaction
.10
-.37
.10
-.75**
.38
-.90
.25
-2.27
Distribution Factors
Acquired brand provides new distribution resources to the firm
Target bought to leverage acquirer’s distribution resources
.89**
-.12
2.25
-.27
Observations
R2
Adjusted R2
F-value
F-probability
*** p < .01
** p ≤ .05
* p ≤ .10
188
.25
.17
3.37
< 0.01
33
Table 6
Cross-Sectional Regression Results on the Standardized Abnormal Return for the Event
Day for the Brand Disposals (0,0) [In Percent]
Brand-Level, Firm-Level,
Transaction, and Strategic
Logic Factors
Parameter
Estimate
t-value
-.60
-1.42
Independent Variable
Intercept
Brand-Level Factors
Un-relatedness (brand is outside of the firm’s major industry)
Disposed brand’s percent of prior year firm sales
Disposed brand has inferior distribution resources
Geographic presence: USA
Geographic presence: Canada
Geographic presence: U.K.
Geographic presence: France
Geographic presence: Germany
Geographic presence: Italy
Firm-Level Factors
Tobin’s Q
Market value
Transaction Factors
Disposal expected to have an accretive/dilutive earnings impact
Perception of price received (good: 1, poor: -1)
Strategic Logic
To focus on faster growing brands
To focus on more profitable brands
To focus on core brands
To reduce debt
To buyback shares
.51*
20.20***
2.22***
.22
-.17
.05
.73*
.44
-.45
.08
.00
.55
.30
.90**
1.48**
2.19
2.46
.23
-.59*
.07
-1.01*
.78
Observations
R2
Adjusted R2
F-value
F-probability
*** p < .01
** p ≤ .05
* p ≤ .10
.91
-1.87
0.28
-1.75
1.16
128
.41
.32
4.25
< .01
34
1.81
5.65
3.74
.75
-.59
.14
1.70
1.10
-1.11
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