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More often than not, corporate acquisitions are expensive and difficult, especially those transacted for the purpose of advancing the aims of corporate entrepreneurship (CE). Motivated by frequent, high-cost failures, firms are experimenting with novel organizational structures and fresh approaches to acquisition-driven CE. In this study, we examine the effectiveness of corporate spin-ins-acquisitions in which the acquired company is founded by former employees of the acquiring firm-in resolving key challenges of CE-motivated acquisitions Using a matched pair-wise dataset of spin-in and non-spin-in acquisitions, we discover that spin-ins generate superior outcomes, positioning them as a high-potential facet of CE portfolios.
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Bringing It All Back Home:
Corporate Venturing and Renewal through Spin-Ins
This is a Pre-Print of the Manuscript, accepted April 26, 2018, in Entrepreneurship Theory & Practice
See ET&P Site for Final, Citable Version: http://journals.sagepub.com/doi/full/10.1177/1042258718778547
ETP in pdf version: http://journals.sagepub.com/doi/pdf/10.1177/1042258718778547
Richard A. Hunt -- Primary Contact
Virginia Tech
Pamplin College of Business
Blacksburg, VA 24061
rickhunt@vt.edu
(720) 334-8685
David M. Townsend
Virginia Tech
Pamplin College of Business
Blacksburg, VA 24061
dtown@vt.edu
Elham Asgari
Virginia Tech
Pamplin College of Business
Blacksburg, VA 24061
easgari@vt.edu
Daniel A. Lerner
Universidad Deusto
Bilbao, Spain
daniel.lerner@colorado.edu
Acknowledgements: We wish to thank Thomas Keil and Johan Wiklund, as well as the
anonymous reviewers for their insights and recommendations, all of which were highly
instrumental to the improvement of this work.
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Bringing It All Back Home:
Corporate Venturing and Renewal through Spin-Ins
ABSTRACT
More often than not, corporate acquisitions are expensive and difficult, especially those
transacted for the purpose of advancing the aims of corporate entrepreneurship (CE). Motivated
by frequent, high-cost failures, firms are experimenting with novel organizational structures and
fresh approaches to acquisition-driven CE. In this study, we examine the effectiveness of
corporate spin-ins – acquisitions in which the acquired company is founded by former employees
of the acquiring firm – in resolving key challenges of CE-motivated acquisitions Using a
matched pair-wise dataset of spin-in and non-spin-in acquisitions, we discover that spin-ins
generate superior outcomes, positioning them as a high-potential facet of CE portfolios.
Key Words: Corporate Entrepreneurship; Corporate Venturing; Spin-ins; Acquisitions; M&A
1. INTRODUCTION
While much of CE literature has focused on the antecedents and outcomes of internal efforts
to mobilize resources towards the achievement of internal CE initiatives (Covin & Miles 1999;
Zahra, Nielsen & Bogner 1999), corporate acquisitions are a popular, high-profile attempt to
jump-start CE aims through the mobilization of external resources and capabilities (Hudson
1994; Schildt, Maula & Keil 2005). CE pursued through corporate acquisitions faces a well-
documented set of challenges, known collectively as the “M&A paradox” (Cording et al. 2002;
Sirower, 1997), a notion underscoring the problems firms face in CE when attempting to buy and
integrate novel technologies and organizations profitably and efficiently through corporate
acquisitions (Agrawal & Jaffe 2000). Existing research on M&A suggests that, on average,
acquisitions destroy acquiring firm value (King, et al. 2004). The principal reason for this lies in
the tendency of acquiring firms to pay acquisition premiums that are not justified by the revenue-
side and expense-side synergies that are ultimately realized (Cartwright & Schoenberg 2006).
Firms have been hard-pressed to solve the M&A Paradox, even while corporate acquisitions
continue at a torrid pace (Deloitte 2018). There are, however, signs of change (McCarthy &
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Dolfsma 2012). Cognizant of the challenges posed by acquisition-driven CE, acquiring firms
increasingly have experimented with new approaches to the efficient organization of acquired
assets (Faulkner, Teerikangas & Joseph 2012; Michl, Gold & Picot 2012). Despite these
emerging trends, scholarly research has lagged in identifying and assessing the effectiveness of
these novel organizational forms. For example, Dess et al. (2003) notes the lack of research on
alternative structures for CE pursuits. Phan and colleagues (2009) similarly emphasize
tendencies to ignore important heterogeneities of CE organizational forms and processes.
Responding to the need for new perspectives on the organizational structures, processes, and
governance of CE, the purpose of this study is to explore whether and how spin-ins enable
acquiring firms to achieve stronger CE outcomes. Corporate spin-ins occur when a firm acquires
a company that was founded by a former employee. Often, the innovations of ex-employees are
permanently lost to the parent-firms when frustrated or ambitious employees leave the parent to
form their own companies (Hunt & Lerner, 2012; Klepper & Sleeper 2005), a phenomenon
called intra-industry entrepreneurial spinouts. Such spin-outs typically fail to facilitate corporate
renewal since the parent company does not benefit from the innovations produced in the new
organization (Agarwal, et al. 2004; Hunt, 2013b).
In some cases, however, these spin-outs are later acquired by the parent-firm, thus
reintegrating the ex-employees, along with their knowledge-based assets, back into the parent
organization. Acquiring innovation in this fashion is known as a spin-in. Though largely ignored
in research to-date, the phenomenon is becoming an important facet of CE external venturing
portfolios in sectors characterized by rapid technological change and relatively limited barriers to
entry. The question is: Do these novel attempts to pursue external sources of CE reverse the
tendency for corporate acquisitions to destroy shareholder value for the acquiring firm?
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Using a matched-pair design, consisting of spin-in and non-spin-in acquisitions completed
between 1995 – 2012, we investigate the extent to which spin-ins enhance the efficient
organizing aims of CE initiatives over traditional forms of M&A. Although many firms
experiment with alternative strategic initiatives in the CE context, the long-term viability of such
approaches hinges directly on whether these strategies achieve the aims of efficient organizing
(Williamson, 1985). Inefficient organizational forms, regardless of how much innovation value is
created through CE initiatives, will not survive long in competitive markets if resources are
wasted (Cloodt, Hagedoorn & Van Kranenburg 2006).
Our study addresses these issues by providing the first comprehensive scholarly treatment of
corporate spin-ins. Extending theoretical arguments grounded in the transaction cost logics of
efficient organizing (Williamson 1985) and the existing literature on acquisitions (Cartwright &
Schonberg 2006) we evaluate the key moderators that ultimately dictate the extent to which
acquisitions create or destroy shareholder value (King et al. 2004): information asymmetries,
executive hubris, and post-acquisition integration. This approach enables us to examine the
viability of spin-ins as a novel form of efficient organizing, and the effectiveness of efforts to
pursue CE efficiently and profitably through acquisitions (Sagner 2012; Steger & Kummer
2007). Insofar as spin-ins leverage pre-existing ties between the acquirer and target, our study
indicates that they have the potential to shed new light on the value-creating and value-
destroying consequences of efforts to pursue CE through corporate acquisitions.
2. THEORETICAL DEVELOPMENT
The Challenge of Corporate Entrepreneurship through Acquisitions
Regardless of firm size or age, innovation is elusive, complex and fluid (Fleming & Sorenson
2012), requiring firms to develop or obtain highly specialized creative assets. Due to the
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challenges of innovating through the development of internal resources and capabilities, firms
often turn to external sources of renewal (Floyd & Wooldridge 1999; Hitt, Hoskisson & Ireland
1990), through organizational structures ranging from joint ventures, alliances, R&D agreements,
and product licensing, to outright acquisition. Each of these external development pathways
creates a wide array of situation-dependent costs and benefits (Heeley, King, & Covin 2006) and
knowledge spillover effects (Covin & Miles 1999) that will impact the long-term capabilities
(Sirower 1997) and profitability (Agrawal & Jaffe 2000) of the transacting parties. The largest
and the riskiest of these external approaches to CE are corporate acquisitions, which now exceed
$5 trillion in aggregate annual deal values (SDC 2017). Acquisitions are the quintessential
attempt to use external markets to buy rather than build new capabilities (Heeley et al. 2006).
However, the scorecard on CE strategies pursued through the acquisition of external resources
is generally bleak. As King et al. (2004:196), concluded: “After decades of research the
overwhelming conclusion must be that M&A activity, on average, does not positively contribute
to an acquiring firm’s performance.” Moreover, the returns to acquiring firms have steadily
deteriorated over the past fifty years. Even the best explanatory models for the heterogeneity of
acquirer returns exhibit large unexplained variance (Cartwright & Schoenberg 2006), exceeding
70% (Stahl & Voigt 2005). This forms the basis of what has been dubbed the “M&A Paradox”
(e.g. Agrawal & Jaffe 2000). Simply put, the “M&A Paradox” holds that despite virtually all
extant research demonstrating that corporate acquisitions, on average, fail to create shareholder
value (Datta, Pinches & Narayanan 1992; King et al. 2004), tens of thousands of deals and
trillions of dollars are annually transacted (SDC 2017). With rare exception, acquiring firms pay
a significant premium above the prevailing market price for a target firm (Cartwright &
Schoenberg 2006). Although there are many reasons for value destruction, one of the main
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reasons continues to be the high premiums firms pay for acquired assets (Agrawal & Jaffe 2000;
Cartwright & Schonberg 2006). The classic justification for these premiums focuses on
“synergies,” representing the acquirer’s beliefs that integrating the acquirer’s and target’s
business operations will generate incremental value (Sirower 1997). Yet, the persistent
underperformance of acquisition-driven CE poses important challenges for the notion of efficient
organizing in the theory of the firm (Williamson 1985). In particular, the question of why it is
that firms routinely fail to achieve synergies remains a matter of contention for existing
acquisition frameworks (Capron, Dussauge & Mitchell 1998; Hitt et al. 1998).
If the principal rationale in paying hefty acquisition premiums is based on revenue growth and
cost control greater than that which can be achieved independently, then explanatory models for
the returns to acquiring firms must take into account the acquirer’s ability to create post-
acquisition synergies (Capron et al. 1998). Extant research has identified three primary culprits
of this “synergy trap” (Sirower 1997): (i) information asymmetries (e.g. Officer, Poulsen &
Stegemoller 2009), which impair the ex-ante ability to accurately assess synergies; (ii) executive
hubris (e.g. Hayward & Hambrick 1997) which drives excessive acquisition premiums; and, (iii)
integration difficulties (e.g. Birkinshaw, Bresman & Håkanson 2000), which limit the ex post
capacity to achieve synergies. Collectively, these dimensions undermine the long-term quest for
efficient organizing in established companies by raising costs and undermining the CE renewal
efforts through acquisitions (Birkinshaw, et al. 2000; Datta 1991; Yu et al. 2005).
Value-Creation and Efficient Organizing through Spin-in Acquisitions
The inability of acquiring firms to extract value from M&A activity raises important questions
regarding the nature of efficient organizing in the theory of the firm. Yet, novel approaches to
exploring how the three impediments influence the post-acquisition performance of M&A deals
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have been in short supply in both the CE and general M&A literatures. In essence, acquirers
appear to repeat the same mistakes over and over (Agrawal & Jaffe 2000). The use of corporate
spin-ins may be a notable exception. Corporate spin-ins -- involving the acquisition of companies
created by former employees -- offer an opportunity for acquirers to generate superior CE
outcomes by leveraging prior employment ties. This is especially important given that a majority
of acquisitions fail to achieve the expected synergies, thereby undermining the performance
goals of efficient organization in reducing post-acquisition costs (Yu et al. 2005). As noted
above, the failure of most acquisitions to generate positive returns for the acquiring firm is due in
large part to three factors: ex ante information asymmetries, which obscure the true potential of
synergistic relationships between acquirers and targets; executive hubris, which inflates
acquisition premiums; and, post-integration obstacles, which limit the realization of synergies.
The central question in this study is whether spin-ins offer a useful “hybrid” approach, one
capable of addressing these impediments to successful of CE-motivated acquisitions. If so, then
spin-ins may be a viable alternative and a useful facet of a firm’s CE portfolio. Consistent with
findings that apply transaction cost economics (Williamson 1985) to research-driven exploration
(Silverman 1999), harnessing and profiting from innovation does not lend itself solely to rigid
hierarchies (Benner & Tushman 2002) or purely market-based solutions (Hunt, 2013b). As
numerous studies demonstrate, firms that attempt to enact CE exclusively through markets or
hierarchies are beset with numerous organizational inefficiencies, sometimes culminating in
steep financial losses (Datta et al. 1992; Dess & Lumpkin 2005). Instead, resolution of the classic
efficiency concerns facing firms that pursue CE via acquisition may necessitate innovative new
approaches. In this regard, spin-ins offer an alternative: the capacity to conduct CE successfully
through its hybrid features. Spin-ins grow the acquiring form’s innovative capacity while
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resolving transactional impediments to efficient organizing. Rather than destroying value
through acquisition-driven CE development, the internal-external hybrid features of spin-ins may
endow them with a comparative advantage over acquisitions for which there are no prior ties.
The underlying cause of spin-ins’ performance advantage stems from the ways in which its
hybrid structure leverages pre-existing ties, thereby minimizing the barriers to effective and
efficient organizing for CE. In theory, prior employment ties should be instrumental in deriving
incremental value through a more effective realization of relational exchange (Dyer & Singh
1998), one that cannot be replicated by entities that do not share the kinds of prior ties that
facilitate mutually beneficial exchange (Emerson 1976). Thus, we hypothesize that overall:
H1: Spin-in acquisitions will, on average, out-perform non-spin-ins.
Next, we will deal in more granular fashion with the ways in which spin-ins may
attenuate the impact of three well-documented impediments to successful acquisitions:
information asymmetries, CEO hubris, and post-acquisition integration.
Spin-ins and Information Asymmetries
Even under the best circumstances, acquisition-related due diligence is performed under a
multitude of constraints, primarily stemming from incomplete information (Officer, et al. 2009).
Information asymmetries have been shown to undermine firm efficiency objectives since
acquisitions, by their very nature, constitute a terminal sale for which the buyer bears the risk of
overpayment (Reuer 2005). This is particularly true when acquiring small and new firms, which
may not possess the resources or inclination to maintain reliable accounting systems (Shen &
Reuer 2005). Even when financial and operational performance disclosures are exemplary, the
tacit knowledge and underlying capabilities of an organization are rarely available for unbiased
review (Singh & Zollo 1998). As a consequence, intentional and unintentional information
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asymmetries arise that may have a marked impact on the valuation of a target entity. This may,
in turn, lead to a miscalculation of the opportunities to achieve revenue and cost-control
synergies. To the extent that the quantity and quality of information can be improved during the
due diligence process, acquirers may avoid paying excessive acquisition premiums.
Theories of relational contracting in the theory of firm suggest that “[…] informal agreements
sustained by the value of future relationships” -- including those between employer and
employee -- generate reciprocity and promote trust among the actors involved in the exchange
(Baker, Gibbons, & Murphy, 2002: 39). Since trust can substitute for costly contracts and
expensive monitoring requirements, such ties are economically efficient (Milgrom, 1988).
Information asymmetry involving uncertainty about a start-up’s quality and trustworthiness
usually leads acquiring firms to spend excess resources performing due diligence (Perry & Herd,
2004) and may even constrain the efficacy of due diligence. Conversely, embedded ties allow
access to more reliable, less expensive information, which minimizes the adverse effects of
expensive uncertainties (Carson, Madhok, & Wu, 2006). Strong relations provide notable
benefits in the pursuit of resources, information, and status (Ketchen, Ireland & Snow 2007).
Building upon this notion of relational contracting, spin-ins should hold an advantage over
non-spin-in acquisitions, which lack the impact of mutual social norms and prior social ties. By
virtue of the ability to leverage existing relationships, acquirers of a spin-in should be in a better
position to access critical information regarding the financial and operational prospects of the
target firm. We would expect these improved optics to result in comparatively better acquisition
outcomes for the acquiring firm. Accordingly, we predict that spin-ins will favorably moderate
the adverse effects of information asymmetries:
H2: The use of spin-ins as a mode of acquisition will attenuate the negative
relationship between asymmetric information and acquisition performance.
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Spin-ins and Executive Hubris
As noted above, even the best M&A models account for only one-third of the heterogeneity in
acquisition outcomes; and yet, durable predictors have been identified, one of which is the role
of the CEO in setting and implementing an acquisition strategy. Researchers have shown that
over-confidence in the CEO of the acquiring firm accounts for a portion of the excess premiums
paid in value-destroying acquisitions (Ferris, Jayaraman & Sabherwal 2013; Hayward &
Hambrick 1997). This occurs because hubristic managers have a tendency to overestimate their
ability to identify and create post-acquisition synergies. Malmendier and Tate (2005) showed
that CEOs meeting the definition of “arrogant” were 2.5 times more likely to consummate a
value-destroying acquisition.
Overconfidence also leads to a number of acquisition-related maladies, including wasteful
expenditure of resources, over-investment in unsuccessful firms (Zacharakis & Shepherd 2001),
competitive blind spots (Ng, Westgren & Sonka 2009), and overvaluation of businesses
(Hayward & Hambrick 1997). CEO overconfidence, which is rooted in self-attribution bias
(Doukas & Petmezas 2007), to a "better-than-average" effect (Malmendier & Tate 2005) that
encourages CEOs to trust their own judgments, even in complex, high-risk decision-making
contexts, even when that may be ill-advised (Ferris et al. 2013).
In the case of spin-ins, many of the elements that drive judgment and valuation errors
stemming from over-confidence may be substantively attenuated. For example, CEOs at firms
such as Cisco have made spin-ins a core facet of their CE portfolio. This stems from recognition
at the very top of the company that the acquisition of firms launched by former employees
involves “spinning in” innovation that previously “walked out the door” (Klepper & Thompson
2010). So, even while CEO hubris and narcissism (Chatterjee & Hambrick, 2007) may also
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inflate premiums paid for spin-ins, these effects are likely to be at least partially mitigated by the
attenuation of judgmental errors that otherwise arise through acquisition-driven CE. By
recognizing the value created by former employees outside the domain of the parent-firm, CEOs
who are receptive to spin-ins can leverage the familiarity acquirers enjoy with the target firm.
CEOs who view ex-employees with receptivity rather than enmity have the potential to reduce
deal-specific uncertainty and complexity, which in turn enables these CEOs to calibrate their
decisions more effectively to the decision environment (Li & Tang, 2010), generating more
realistic valuations. In these cases, hubristic CEOs may be less likely to overpay for spin-ins
(Narayanan, Yang & Zahra 2009), which would favorably influence acquisition outcomes.
H3: The use of spin-ins as a mode of acquisition will attenuate the negative
relationship CEO Hubris and acquisition performance.
Spin-ins and Post-Acquisition Integration
Once an acquisition is consummated, the process of integrating the acquired firm begins.
Extant research across industries suggests that this process is often time-consuming, challenging,
and expensive (Datta1991; Vaara 2003; Yu et al. 2005) due to the tendency of organizational
systems to resist change (Cyert & March 1963). Evolutionary economics holds that firms have
durable capabilities and routines that persist over time (Nelson & Winter 2009; Dosi, Nelson &
Winter 2000). Routines make up the most important form of an organization’s specific
operational capabilities and are a crucial facet of efficient organizing (Cyert & March 1963,
Nelson and Winter 2009). For instance, in this vein, Wezel, Cattani and Pennings (2006)
emphasize the negative consequences of parent firms confronting the loss of firm specific skills,
routines, and resources, such as the social capital and creative capacity of departing employees.
The reintegration of former employees might also be a more complex issue than other culprits
of synergy trap. While our theory predicts that spin-ins will generate benefits to acquirers with
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respect to information asymmetries and CEO over-confidence, it less clear whether acquisition
integration – the third component of the “synergy trap” articulated by Sirower (1997) – will
create similar benefits. Improvements in the reliability of information should reduce the risk that
an acquirer will perform inadequate or inaccurate due diligence. Familiarity emanating from
prior ties and embedded relations should at least partially mitigate the risk of excess premiums
due to CEO hubris. However, the organizational and cultural impacts of spin-ins are complicated
by their tendency to create massive compensation disparities (Alles & Alles 2002) as a
consequence of purchasing spin-in assets and thereby enriching former employees of the
acquiring firm. Even under the best circumstances, incumbent employees can be mistrustful of
the organizational developments surrounding acquisitions (Sears & Hoetker 2014) out of fear
that the net effect will negatively impact their respective careers (Greenwood, Hinings, &
Brown, 1994). Such sentiments have been closely associated with the failure to properly
integrate post-acquisition (Hambrick & Cannella, 1993; Larsson & Finkelstein, 1999).
Conversely, the reintegration of employees through spin-ins may generate positive benefits by
reacquiring the knowledge of ex-employees and leveraging the interpersonal ties that create
barriers for effective post-acquisition integration (Birkinshaw et al., 2000; Blake & Mouton
1985). A firm’s tacit knowledge can be team-based and socially embedded (Nelson & Winter,
2009), but also it exists in individual human capital (Berman, Down & Hill 2002; Hitt, et al.
1998). As employees internalize an organization’s culture and social norms (Meek 1988; Pablo
1994), they absorb procedural and declarative knowledge related to functional capabilities, such
as R&D and marketing, while also generating a key relational mechanism that can reduce firm
organizing costs (Baker et al., 2002). Consequently, spin-ins may hold certain advantages in their
capacity to foster the reintegration of tacit knowledge to the parent firm due to the relational ties
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between the parent firm and the acquisition target. Through this, we expect that reintegrating
former employees through spin-ins will improve acquisition-related outcomes by attenuating the
challenges of melding disparate organizations post-acquisition:
H4: The use of spin-ins as a mode of acquisition will attenuate the negative relationship
between post-acquisition integration problems and acquisition performance.
3. DATA AND METHODS
Since there is no central repository of data on spin-ins, a major undertaking of our study
involved the compilation of spin-in acquisitions. In order to insure an ample population of deals
both with and without extensive prior ties, we focused on sectors with high M&A volume:
software, cloud services, high-tech manufacturing, and electronic gaming. Using Thomson-
Reuters’ Securities Data Company (SDC) Platinum, we focused on transactions between $10MM
and $150MM, consummated by publicly traded firms, from 1995-2012. The cut-off date was set
at 2012 to allow for an extended post-transaction observation window. Deals smaller than
$10MM are often deemed to be non-material from an accounting perspective, which means that
there is little or no public information through SEC-mandated reporting. Meanwhile, deals
greater than $150MM typically involve multi-product or even multi-divisional firms for which
the specific impact of ex-employees is difficult to identify and parse. Robustness tests performed
on wider ranges did not materially affect the results. Only acquisitions by publicly traded firms
were included, since private firms are not generally subject to SEC reporting requirements,
which is necessary for deal-level analysis. These parameters resulted in an initial pool of 7,136
transactions. After screening for errant data due to duplicates, missing data, erroneous data, and
acquisitions by private companies, the sample was reduced to 6,780 transactions.
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Using Lexis-Nexis, PRNewswire, Reuters M&A, MarketWatch.com, and DowJones News,
we searched for prior employment ties through a four-step process. First, we searched news
sources for mention of the acquisition, yielding 6,453 transactions. Second, we searched these
texts for any mention of the acquired firm’s executives, yielding 5,881 transactions. Third, we
screened for mention of prior association with the acquiring company, which produced a pool of
527 transactions. Fourth, we validated 464 deals with prior ties, through a combination of
additional news sources (104 validations), SEC filings (57 validations), and LinkedIn.com (303
validations). Although LinkedIn was founded in 2003, it now has more than 500 million
members, representing the single largest repository of individual-level professional information
available. 14 of validations were later excluded because the prior ties appeared to involve
previous work as a consultant or contractor to the acquiring firm rather than a full-time
employee. This final adjustment resulted in 450 acquisitions of firms founded by ex-employees
of 203 parent-firms, 1995-2012. For the purpose of constructing a pairwise set, we matched 450
non-spin-in acquisitions consummated by 206 acquiring firms, drawn from the pool of 5,354
non-spin-in transactions. The final set of 450 matched pairs of spin-in and non-spin-in
substantively reflected all key characteristics of the larger transaction pool, as discussed below.
Dependent Variable
For decades, the elusiveness of an appropriate dependent variable has hindered efforts to
assess M&A value creation and destruction accurately. The tools that are most often used to
calculate shareholder value created or destroyed, such as Cumulative Abnormal Returns (CAR)
and Tobin’s Q, are challenging to employ outside the immediate window surrounding the public
announcement of transactions (Agrawal & Jaffe 2000). Very short timeframes, consisting of
days, weeks or even months, post-transaction, may fail to account for the realization of synergies
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occurring over several years of organizational integration. Conversely, the use of CAR for longer
timeframes is inherently “noisy” as numerous non-systematic forces substantially impact the
market returns over the course of years. For example, Cisco Systems completed 58 acquisitions
from 1995 to 2000, including 19 in 1999, alone. It is untenable to consider the CAR of each
acquisition independent of the others, let alone to do so for five or more years. This is likely to
be one of the key reasons that existing models exhibit a persistently high unexplained variance.
Either the timeframe is too short to capture long-term synergies, or the timeframe is too long to
be able to isolate acquisition-specific effects.
Acquirer Asset Impairment (AAI): As an alternative to address these short-comings, our
research design involved the development of a transaction-specific measure with far greater
exactitude for our study’s end-point: Acquirer Asset Impairment (Alciatore, Dee, Easton & Spear
1998; Boennen & Glaum 2014; Hayn & Hughes 2006; Zucca & Campbell 1992), which stems
from reporting requirements consequent to Statement of Financial Accounting Standards No. 142
(SFAS 142), concerning “Goodwill and Other Intangible Assets” (Bens, Heltzer & Segal 2011).
AAI is significantly more precise than either CAR or even Tobin’s Q in pinpointing acquisition-
specific under-performance (Alciatore, et al. 1998; Boennen & Glaum 2014). Functionally, an
asset write-down is required when the actual cash flows generated from acquired assets fail to
achieve the levels used to justify the purchase price of the assets. In the accounting literature,
write-off disclosures have been shown to be particularly useful in providing information about
decreases in an asset’s economic value (Francis, Hanna & Vincent 1996) and information
relating to changes in management strategies (Brush & Artz 1999).
Our study operationalizes AAI as a categorical indicator for the occurrence of any material
diminution in the value of acquired assets (identified through SEC disclosures in edgar.com) in
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the first five years post-transaction. More than 90% of all acquisition-related intangible asset
write-downs occur within the first three years, and more than 99% occur within the first four
years (Barth & Clinch 1998; Riedl 2004), giving us a high degree of confidence that our
observation window conservatively accounted for virtually all write-downs. A value of “1” was
assigned for conditions in which the FASB standard for “material impairment” triggered an asset
write-down in recognition of acquisition-related underperformance within five years of the
acquisition. If no asset impairment occurred within the first five years post-acquisition, then the
transaction was coded “0”. For example, HP’s $11 billion acquisition of the cloud computing
firm, Autonomy Corp. in 2011, consisted almost exclusively of goodwill and other intangibles in
anticipation of significant revenue synergies between the combined corporations. By 2013, it was
clear that virtually none of these synergies would materialize and HP was forced to write off $9B
of goodwill related to the Autonomy purchase. Such an acquisition, when fitting within the
aforementioned sampling parameters, would be coded as “1”.
Independent Variables
Acquisition Type (AT). The focal predictor of our analysis is AT, which is a discrete
dichotomous variable, coded as “1” to indicate that an acquisition was classified as a spin-in,
meaning that one or more of the target’s founders were prior employees of the acquirer. As
detailed above, information on founders’ employment histories was drawn from and vetted with
a combination of sources, including acquirer press releases, target web sites and LinkedIn.
Information Asymmetry (IA). Reuer and Ragozzino (2008) demonstrated that dyadic
relationships between acquirers and targets reduce information asymmetries. Similarly, Dyer and
Singh (1998) posited circumstances under which pre-existing relations reduced transaction costs
and substantively enhanced trust and exchange value between parties. Specifically, in the context
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of acquirer-target social ties and merger outcomes, Ishii & Xuan (2014) used prior associations
to proxy information asymmetries. Our study uses the Ishii-Xuan approach in the comparative
analysis of spin-ins and non-spin-ins, by measuring IA as the frequency and duration of prior ties
calculated as the years of shared association between the target’s founders and executives of the
acquiring firm. Since we collected more exhaustive data than Ishii and Yuan, we were able to
add professional and industrial ties rather than the educational ties they used in their approach.
CEO Hubris (CEO) is an indexed measure of CEO over-confidence. As discussed above,
existing literature on M&A has identified the CEO’s central role in the decision-making
processes that culminate in corporate transactions, with special attention given to the potent
influence of CEO hubris (Ferris, et al. 2013; Hayward & Hambrick 1997, Malmendier & Tate
2005) We employ the methodology developed by Hayward and Hambrick (1997) in the context
of M&A decision-making. The index, which has been used widely in management research (e.g.
Chatterjee & Hambrick 2007; Li & Tang, 2010), consists of three components: the acquiring
company's recent financial performance, drawn from Edgar; recent media praise for the CEO,
determined through a compilation of positive LexisNexis articles; and, a measure of the CEO's
self-importance, calculated through a combination of each CEO’s relative pay, drawn from
company’s proxy statement, and the CEO’s portrait size as published in the firm’s annual report.
Hayward and Hambrick (1997) provide further operationalization details.
Post-Acquisition Integration (PAI), is a discrete dichotomous variable (Pablo 1994),
based on Datta’s (1991) technique of assigning the degree of operational integration as a function
of the acquired firm’s consolidation into existing operations. However, while Datta used
employee surveys, we examined the integration decisions directly through information on each
firm, using SEC Filings (i.e. 10K through Edgar), PR Newswire, and LexisNexis. An assignment
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of “1” indicates that the acquired entity was fully integrated into the existing divisional structure
of the acquirer. “0” indicates an autonomous division with a direct line of reporting to the
corporate executive committee. “1” indicates a largely integrated entity, wherein the acquired
products and services are integrated into the service and product offerings of the acquirer. Using
this schema, each of the 450 spin-in acquisitions and 450 non-spin-in acquisitions were assigned
a value of either “1” or “0,” indicating, respectively, if the acquired entity was substantively
absorbed into the acquirer’s existing structure or was allowed to operate as a division unto itself.
Control Variables
To ensure our results were not simply an artifact of known M&A effects, our logit model
includes widely recognized covariates pertaining to acquisition outcomes, consistent with well-
cited empirical approaches (Agrawal & Jaffe 2000; Sirower 1997), and meta-analyses (Bruner
2002; King et al. 2004). These controls consist of conglomeration effects, business relatedness,
method of payment, and prior acquisition experience.
Conglomeration, which is generally associated with poor acquisition outcomes (Bruner
2002; Sirower 1997) is a discrete dichotomous variable, coded as “1” for firms maintaining a
diversified portfolio approach to business holdings, such as General Electric. Conglomerates
typically fail to achieve anticipated acquisition-related revenue and expense synergies (King et
al. 2004). As Bruner (2002: 56) note, “Diversification destroys value. Focus conserves it.”
Relatedness. Existing literature holds that greater relatedness between the acquirer’s and
target’s main business lines is favorable to acquisition outcomes (Hayward & Hambrick 1997).
Conversely, unrelatedness is often value-destroying. Berger and Ofek (1995) found that
acquirers routinely incur acquisition-related losses exceeding 15% when the target firm is not in
the same industry. Following Wang and Zajac (2007), we captured this determining factor for
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each acquisition through a business distance calculation, based on the difference between the
five-digit NAICS codes for the acquirer and target.
M&A Experience. Existing studies of M&A success rates also have taken note of the
benefits acquirers accrue through prior acquisition experience (Bruner 2002), especially when
that experience is gained through the consummation of similar acquisitions in similar businesses,
such that learnings are likely to be improved (Trichterborn, Knyphausen-Aufseß & Schweizer
2016). Experience was captured as a dummy coded variable, with “1” indicating prior
acquisition experience of similar size and in the same three-digit NAICS code.
Payment Method. Research has demonstrated that acquisition outcomes are also highly
correlated with the payment method, such that greater amounts of cash tend to result value-
creation more frequently than non-cash acquisitions. We identified method of payment through
SDC, using the approaches developed Chang (1998) and Martin (1996). Both studies found that
stock-based deals are associated with significantly negative acquirer returns.
Goodwill. From an accounting perspective, goodwill consists of the acquisition price in
excess of identifiable assets; in essence, the cost of an acquired firm’s prospects. Existing
research has shown that the farther acquirers stray from focusing on identifiable value by
“betting on the come,” the greater the likelihood of money-losing acquisitions (e.g. Rau &
Vermaelen 1998). Bruner’s meta-analysis (2002) revealed that acquisitions with a high percent
of intangible assets, suffer losses averaging 17% of the acquisition cost. Consistent with
Boennen & Glaum (2014), Bruner (2002), and others, we control for goodwill by measuring
intangibles as a percentage of the total acquisition cost, using data from SDC.
Acquirer Ownership of Target. Over and above the prior ties captured in the variable for
IA, we control for parent-company sponsorship by coding “1” when target firms received prior
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equity investment from the acquiring firm. An existing equity stake allows for enhanced
knowledge regarding the financial and operational state of the acquired firm (Kumar 2009).
Model Specification
Given the dichotomous nature of the dependent variable and the desire to preserve
interpretability of the model coefficients as an odds ratio, our model estimated maximum
likelihood, using binomial logistic regression, structured as follows:
Acquirer Asset Impairment = b0 + β1 AT + β2 IA + β3 CEO + β4 PAI + β5 AT*IA +
β6 AT*CEO + β7 AT*PAI + g Controls + ε.
The model estimates the likelihood of an acquirer experiencing a failed acquisition (i.e.
recognizing an asset impairment within the first five years post-acquisition) as a function of
acquisition type (spin-in or non-spin-in) and our three hypothesized interaction terms, derived
from well-established impediments to successful acquisitions (King et al. 2004).
As a binary logit that employs dichotomous predictors, our model analysis took careful note
of potential confounds related to limited dependent variable (LDV) methods, as elaborated by
Wiersema and Bowen (2009). Methods research in management has shown that this is
particularly important for the interpretation of moderating effects in LDV models, which require
analysis of the marginal impact on the DV (Hoetker, 2007; Bowen & Wiersema, 2004;
Wiersema & Bowen, 2009). Since the size of the interaction variable coefficient (i.e. the
coefficients for H2, H3 and H4, captured through the product terms: AT*IA, AT*CEO, and
AT*PAI) does not itself indicate the size effect of the interaction on the probability that asset
impairment will occur, it is necessary to analyze each interaction’s marginal effects, which we
compute as the discrete change in the probability of impairment, while holding all other variables
fixed (Bowen & Wiersema 2004).
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Matched Pair Design
As noted above, our research design involved a matched pair-wise analysis of 900
transactions drawn from spin-ins and non-spin-ins. Pair-wise matching insured equivalent means
and variance for each focal covariate, so that the paired transactions resembled one another in all
respects other than prior employment ties. The purpose of employing pair-wise analysis with
data drawn from matched sets is to remove bias in the comparison of groups by ensuring equality
of distributions of the matching covariates we employed (Casella 2008; Hunt & Kiefer, 2017;
Stuart 2010). The matched set comparison was constructed while controlling for 9 separate
dimensions (Table 1). With pair-wise matching, the null hypothesis is that there are no
significant differences between the paired subjects, confirmed through t-tests (Cooper, Schindler
& Sun 2006; Hunt & Kiefer, 2017). T-test scores for each of the nine dimensions across the two
matched set pools ranged between 0.11 and 0.92, confirming that the pools were statistically
indistinguishable aside from the existence of prior employment ties for the spin-in pool.
The basic idea of matching is to select from the reservoir of non-spin-ins those acquisitions in
which the distribution of the variables affecting the outcome variable is as similar as possible to
the distribution of the spin-in acquisition. To do so, we employed the propensity score matching
method of Rosenbaum and Rubin (1983). The matching technique generates results that are more
reliable than those derived from a simple comparison in an un-matched sample (Hosmer,
Lemeshow & Sturdivant 2013). By pairing spin-in acquisitions with non-spin-ins that replicated
one another in all important respects, save the acquisition type, we employ a version of the
“nearest neighbor” technique (Pinker 2011; Rosenbaum & Rubin 1983), in which each known
spin-in is assigned a match in accordance with the difference minimizing criteria detailed in
Table 1, through the t-test matched pairing process performed in SPSS.
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[INSERT TABLE 1 ABOUT HERE]
The use of matched samples has extensive precedence in management when scholars have
sought to make targeted comparisons of phenomena that are not conducive to experimental
conditions, such as environmental performance and profitability (Russo & Fouts 1997), TQM-
related stock market returns (Hendricks & Singhal 2001), venture capital firm impacts on
portfolio firms (Lerner 1996), comparisons of exporting and non-exporting small firms
(Westhead 1995), and even studies directly related to tracking M&A performance (e.g. Grote &
Umber 2006; Ragozzino 2016). These, and other studies have employed matching techniques
designed to achieve the greatest possible similarity for the most relevant dimensions of the focal
phenomenon. For example, a study of “best company” rankings by Fulmer, Gerhart and Scott
(2003:991) started with the top-100 listings and then sought to assign to each “a comparison firm
that was the closest suitable match given a set of constraining criteria,” using age, size, and
industry. Our approach also starts with a known set – ours consisting of 450 spin-ins -- to which
we apply specific matching criteria (Table 1). We employ the methods developed by Barber and
Lyon (1997) and used by Loughran and Ritter (2004), each of which also sought to assess
operating performance between pairs that were matched using financial criteria.
Robustness
As with all retrospective analyses, this study involves design elements that require careful
assessment with respect to robustness. The use of matched sets and pair-wise analysis helped to
mitigate the risk of biased predictors by providing controlled comparisons. As noted earlier, the
pair-wise design fulfills several important methodological aims that improve the robustness of
the results. Most importantly, the pair-wise assignments were used to insure that the matched sets
are indistinguishable from one another. Secondly, we sought to create a dataset that could
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provide statistically validated assurances that the results were not simply an artifact of the
differentiation between spin-ins and non-spin-ins. Finally, the pair-wise structure of the matched
sets provided necessary support for the claims suggested by our theory concerning the pursuit of
CE aims through external, acquisition-driven initiatives. By using pair-wise matching we control
for group differences that might otherwise render comparisons spurious (Hunt & Kiefer, 2017).
As an additional safeguard, robustness tests were performed to insure that the results were not
subject to the potentially confounding effects of endogeneity and right-side truncation. As with
most studies in which both the business strategies and the outcomes of those strategies are
included in the analysis, our research design is susceptible to endogeneity on three fronts:
omitted variables, reverse causality, and errors-in-variables bias. To assess the possible presence
of omitted variables, we used the Heckman two-step procedure (Heckman 1979). Applying
Heckman, we generated an inverse Mills ratio that indicated no biasing effects due to omitted
variables. As for reverse causality, we used lagged time-series variables to confirm the
directionality of focal effects (Davidson & MacKinnon 1992). We also performed a Hausman
test (1978), which confirmed that the model predictors are not subject to errors-in-variables bias.
4. RESULTS
The primary purpose of our investigation was to ascertain whether or not the pursuit of CE
through corporate acquisitions is favorably or unfavorably impacted by the development and use
of hybrid organizational forms and novel deal structures; specifically, spin-ins. Our research
design centered on a matched, pairwise analysis of 900 acquisitions, split evenly between spin-
ins and non-spin-ins. The descriptive statistics for acquirers and target firms in Table 1, above,
reveal a number of important facets of the sample and the characteristics of spin-in transactions.
On average, spin-ins are still young firms, with an average age of 3.5 years. Conversely,
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acquiring firms are, on average, large ($15.6 billion), fairly well-established (mean age of 23.2
years) firms, with some prior experience undertaking acquisitions (mean of 3.56 deals). The
acquisitions were financed primarily through the issuance of equity, with goodwill representing
more than 70% of purchase price, meaning that the overwhelming preponderance of each
purchase involved intangible assets, which is typical of innovation-driven, knowledge-based
high-tech sectors (Contractor 2000; Trautwein 2013). In sum, acquiring firms generally purchase
spin-ins with stock while the target firms are still in the start-up phase. The primary source of
value is knowledge-based assets, indicated by the high-level of goodwill.
Table 2 presents a correlation matrix for the variables comprising the analytical models used
in the study. The directionality and magnitude of the correlations is consistent with our central
assertions about the relationships between CE, corporate acquisitions, and the role of spin-ins. In
particular, our measure of acquisition outcomes, AAI, is significantly correlated with Acquisition
Type. Consistent with our central thesis, spin-in transactions are associated with a decrease in the
likelihood that an acquirer will experience acquisition-related impairment.
[INSERT TABLE 2 ABOUT HERE]
Spin-In Performance
Our analysis proceeded in two stages, starting with the main effect of spin-ins on acquisition
performance, followed an examination spin-ins’ marginal effect on three prominent impediments
to successful acquisition-driven CE: information asymmetries (Ravenscraft & Scherer 1987),
executive hubris (Hayward & Hambrick 1997), and organizational integration (Vaara 2003).
Hypothesis 1 predicted that spin-ins will, on average, out-perform non-spins. We tested this
by identifying and quantifying all AAIs occurring within the first five years post-acquisition. As
indicated by the matched set comparison (Table 3) this main effect hypothesis finds support.
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Spin-ins out-performed non-spins by a considerable margin, resulting far fewer AAIs and far
smaller AAIs when they did occur. For the 450 spin-in acquisitions, 43% resulted in asset write-
offs, which averaged 21% of the purchase price. By comparison, 73% of the non-spin-in
acquisitions resulted in an AAI, which averaged 45% of the purchase price. Put differently, the
non-spin-in pool had 40% more failed acquisitions than the spin-in pool, and the average size of
the asset write-offs was more than double the average for spin-ins. Overall, with an average deal
size of $30MM, non-spin-in AAIs resulted in a $4.5B negative impact on acquiring firms,
compared to a $1.1B negative impact associated with spin-in AAIs.
[INSERT TABLE 3 ABOUT HERE]
This marked effect is reinforced by the logistic regression analysis (Table 4). As a logit model
designed to predict the likelihood of any given acquisition resulting in acquirer losses –
objectively indicated as the formal recognition of an impaired asset positive coefficients are
logged values of parameters that increase the likelihood of an AAI, while negative coefficients
indicate less likelihood of an AAI. Pertinent to H1, predicting superior performance by spin-ins,
we would expect that the parameter Asset Type (AT), which is coded as “1” for all spin-ins, will
be negative if in fact spin-ins reduce the likelihood of an AAI. A one degree-of-freedom model
comparison (Judd, McClelland & Ryan 2011) comparing a baseline model, consisting of well-
established control variables (Model 1), with one containing the variable AT, reveals a parameter
estimate for AT that is a statistically significant predictor of acquisition outcomes (
b
= -0.87, p <
.001). By exponentiating the coefficient, we can generate an odds ratio for AT, of 0.419,
meaning that, all else held equal, there is a 58% lower likelihood of an AAI occurring with spin-
ins. In Model 4, which contains three well-known impediments to successful acquisitions (IA,
CEO & PAI), the parameter estimate for AT (
b
= -0.92, p < .001) remains statistically
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significant, indicating that acquirers of spin-ins face substantially less risk of an AAI. Overall,
these logit model findings support the matched set AAI data presented in Table 3, confirming
H1’s prediction that spin-in acquisitions, on average, out-perform non-spin-ins.
[INSERT TABLE 4 ABOUT HERE]
Marginal Effects of Interactions
Having demonstrated that the pursuit of acquisition-driven CE through spin-ins meaningfully
reduces the odds of incurring an AAI, it is important to ask why this occurs. What is it about
spin-ins that make them significantly less prone to value-destroying, failed acquisitions?
Hypotheses 2, 3 and 4, consist of predictions that spin-ins will have a statistically significant
marginal effect in attenuating the most prominent impediments to successful acquisitions. As the
logit model reveals, all three of these variables have statistically significant, positive coefficients
in Models 3 through 8, meaning that each of these three variables increase the odds that an AAI
will occur, regardless of acquisition type. Spin-ins and non-spin-ins are both deleteriously
impacted by IA, CEO, and PAI, under all scenarios comprising our model analysis.
However, our investigation is not interested in average values for all acquisitions, but rather
the specific ability of spin-ins to potentially attenuate some portion of the adverse effects of these
three. Consistent with methods research (Hoetker, 2007; Wiersema & Bowen, 2009) and
comparable empirical studies in entrepreneurship assessing interaction effects (e.g. Drover,
Wood & Payne 2014), we sought to ascertain the “additive measure of unique variation in the
dependent variable that cannot be accounted for by other factors in the analysis” (Pierce, Block
& Aguinis 2004: 919). For this purpose, we developed three variables -- one each for hypotheses
2, 3 and 4 to capture the interaction between AT and the primary obstacles to value-creating
acquisitions, yielding: AT*IA (H2), AT*CEO (H3), and AT*PAI (H4).
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As the logit model results (Table 4) show, regardless of whether these three interactions are
analyzed individually (Models 5, 6, and 7), or collectively (Model 8), each has a statistically
significant, negative parameter estimate, indicating that the interaction effect of each reduces the
risk of an AAI occurring. This is notable since the coefficients for IA, CEO, and PAI are each
positive across the models, which means that on their own they increase the odds of an AAI.
This sign change for the interaction terms suggests that spin-ins (coded as “1” for AT) appear to
attenuate the adverse impact of IA, CEO, and PAI. However, as noted by Wiersema and Bowen
(2004, 2007), this alone is not enough to conclude that there is a statistically significant marginal
effect for each of these interactions in the context of a complete model of predictors. For this
purpose, it is necessary derive the marginal mean of each interaction term for spin-ins and non-
spin-ins across the full range of values, which we present in Table 5.
[INSERT TABLE 5 ABOUT HERE]
As these calculated means demonstrate, spin-ins display a lower probability of AAI for all
interactions and all levels, evidenced by the statistically significant t-tests for each of the nine
mean differences comprising the marginal analysis. For example, Hypothesis 2 predicts that the
use of spin-ins attenuates the negative impact of asymmetric information on acquisition
performance. If correct, then the marginal effect of the AT*IA should indicate a lower
occurrence of AAI in the spin-in condition. The negative coefficient for AT*IA in the context of
logit Model 8 (
b
= -0.58, p < .001) implies an odds ratio of 0.560, suggesting that spin-ins have
the effect of halving the adverse impact of IA. Isolating this term and examining it at low,
moderate, and high levels of asymmetry (Table 5), the spin-in condition for AT*IA reveals a
clear interaction effect when comparing the marginal means.
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In support of Hypothesis 2, this confirms that there is a statistically reliable basis to conclude
that spin-ins materially reduce the occurrence of AAIs by attenuating the negative effects of IA.
Moreover, the impact of spin-ins improves acquisition-related outcomes at all levels of the
parameter IA. Using the graphing approach recommended by Cohen, and colleagues (2003), we
display these effects in Figure 1.
[INSERT FIGURE 1 ABOUT HERE]
For very low levels of prior association, information asymmetry will be more acute (Officer,
Poulsen & Stegemoller 2009), resulting in a higher probability of AAI for both spin-ins and non-
spin-ins. However, non-spin-ins continue to face a far higher AAI rate even as prior association
increases and information asymmetries decrease. As Fig. 1 indicates, the variance in probability
is greater at very high levers of prior association (i.e. lower levels of IA), but this is largely due
to the fact that very few prior associations extended beyond five years.
In similar fashion, Hypothesis 3 predicted that spin-ins will materially attenuate the adverse
impact of CEO hubris, which has been shown empirically to contribute to poor acquisition
outcomes (Ferris, Jayaraman & Sabherwal 2013; Hayward & Hambrick 1997). Our interest,
then, was to determine the marginal effect of spin-ins that can be uniquely attributed to AT’s
interaction with CEO. Here too, the negative coefficient for AT*CEO in the context of logit
Model 8 (
b
= -0.49, p < .001) results in an odds ratio of 0.613, meaning that spin-in acquisitions
will result in AAI’s with about 40% less frequency than non-spin-ins, all else held constant. The
marginal impact of spin-ins on CEO (Table 5) is material and statistically significant. For
example, at moderate levels of CEO hubris – the level at which more than one-third of acquiring
CEOs are situated the AAI probability for spin-ins is 32% versus 61% for non-spin-ins. This
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finding supports Hypothesis 3, as is shown in Figure 2. As the graph indicates, at all levels of
CEO hubris, spin-ins have a lower probability of an AAI.
[INSERT FIGURE 2 ABOUT HERE]
Existing studies on CEO hubris have convincingly demonstrated its strong association with
over-payment for acquired assets. The bivariate correlation in our study for CEO hubris and
intangible assets as a percentage of the acquisitions price is 0.22 (p < .01). Since goodwill
involves the accounting recognition of a purchase price in excess of identifiable assets, it is a
classic instance of betting on the come (e.g. Hayward & Hambrick 1997). Over-confident,
acquisitive CEOs load their respective balance sheets with goodwill from expensive deals.
However, among spin-in acquisitions the influence of CEO appears to be markedly lower.
Functionally, what these differences mean is that the pervasive, unfavorable influence CEO
hubris exerts is substantially mitigated by spin-ins at low, moderate, and high levels.
Our fourth hypothesis (H4) predicted that spin-ins would also be effective at attenuating the
adverse effects associated with the well-established challenges that accompany integrating
acquired entities (Larsson & Finkelstein, 1999; Sears & Hoetker 2014). To achieve targeted
revenue and cost control synergies, acquiring firms must, to some degree, integrate the target
entity; however, full and complete integration runs the risk of throttling the innovation that was
purchased through the acquisition (Hambrick & Cannella, 1993). Thus, acquirers must decide
whether they will fully integrate the acquired firm into existing operations and reporting
structures, or allow for greater autonomy (Graebner 2004). Studies have shown that integration
problems are a primary cause of failed acquisitions (Pablo 1994; Singh & Zollo 1998; Vaara
2003; Yu et al. 2005).
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The results for our test of post-acquisition integration (AT*PAI) are in line with the findings
for H2 and H3, indicating that spin-ins, on average, attenuate negative fallout from acquisition
integration risks. Spin-ins were found to be a statistically significant, favorable moderator of
post-acquisition integration difficulties (
b
= -0.30, p < .01), thereby reducing the odds that
integration challenges will lead to an asset write-down by 26%. Once again, the marginal effects
tell an interesting story. As shown in Table 5, the marginal means for AT*PAI are statistically
distinct at each level. Since PAI is a dichotomous predictor, there are only two levels, low and
high, the former consisting of firms that remain largely autonomous post-acquisition and the
latter consisting of firms that are integrated into one of the acquirer’s existing business units. At
both levels, spin-ins attenuate integration challenges. At low levels of integration, spin-ins have a
positive difference of 0.14, while at high levels of integration the positive spin-in difference
swells to 0.45. This finding supports Hypothesis 4, as is shown in Figure 3. At all levels of the
interaction, spin-ins reduce the occurrence of AAIs.
[INSERT FIGURE 3 ABOUT HERE]
Unlike the marginal relationship across levels for AT*IA and AT*CEO, which exhibit
essentially parallel effects for spin-ins and non-spins, the interaction involving AT*PAI has a
pronounced divergence in the high integration condition. While the probability of an AAI for
non-spin-ins increases from 65% to 84%, in moving from low to high integration, the probability
of an AAI decreases among spin-ins from 51% to 39%. This suggests that that the repatriation of
former employees results in more successful integration of the acquired entities into existing
operations, such that prior ties play a positive role in achieving the synergies that serve to justify
the acquisitions. Rather than the culture clashes and unrealized synergies that often characterize
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the full integration of an acquired entity (Yu et al. 2005), returning employees appear to make
the integration process more effective through the use of spin-ins.
5. DISCUSSION
As noted from the outset, successful acquisitions of any sort are elusive. The pursuit of CE
aims through corporate acquisitions is particularly difficult since CE involves “renewal activities
that enhance a corporation’s ability to compete and take risks” (Phan et al., 2009: 199) –
activities suggestive of novel thinking, focused goals, and an openness to change -- while
acquisitions involve complex transactions, limited information, emotion-laden decisions, and
daunting integration challenges. Despite these and other impediments, large-scale incumbents
increasingly have turned to corporate acquisitions as a primary vehicle to pursue external CE
aims (Cartwright & Schoenberg 2006; Markides 2006). The reality is, however, that vast
majority of these acquisitions have been a source of shareholder value destruction for the
acquiring firms (King et al. 2004; Sirower 1997). Cognizant of the challenges accompanying the
attempt to profitably pursue CE aims through corporate acquisitions, some firms have tinkered
with deal terms, organizational forms, governance modes, and post-acquisition integration
strategies (Birkinshaw et al., 2000; Larsson & Finkelstein 1999). In response to these attempts by
innovation-minded firms to rethink acquisition-driven CE, scholars have called for more research
into the new varieties of both corporate venturing programs (Narayanan et al., 2009) and
organizational forms (Phan et al., 2009).
Taking up this call, the central focus of this investigation involved exploring the extent to
which corporate spin-ins constitute a viable approach to address the numerous pitfalls of external
corporate venturing. Our findings are important for CE theory in several ways. First, important
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links between the CE and strategic entrepreneurship literatures have emphasized that competitive
advantage often rests on the skills and expertise of individuals (Kuratko & Audretsch, 2009), a
disproportionately small percentage of whom constitute the innovative firepower of an
organization (O’Boyle & Aguinis, 2012). Yet, the advantages firms derive from human capital
can be short-lived as the increasing mobility of star performers has increased the likelihood of
corporate spin-outs (Franco & Filson 2006). In response, Markides (2006) suggests, rather than
using resources and managerial talent to grow new businesses inside the organization,
established companies should aim to create, sustain, and nurture a network of feeder firms,
consisting of entrepreneurial firms, each busy colonizing new niches. There are, however, risks
to this approach unless spin-ins are a facet of a firm’s CE portfolio. The benefits of using an
external development strategy is limited by a parent-firm’s ability to reincorporate these “feeder
firms” back into the parent company. Thus, a fundamental contribution of this study is to point to
the existence of a viable, market-based approach for successful, external CE venturing strategies.
Our second contribution extends the frontier of research on M&As by showing how spin-ins
attenuate the negative effects of asymmetric information, CEO over-confidence, and the
substantial challenges posed by acquisition integration process thereby achieving the firm’s aims
of efficient organizing. As the foregoing results demonstrate, spin-in acquisitions out-perform
non-spin-ins by a sizable margin. While the non-spin-in sample in our study experienced
acquisition failure rates in line with the scores of studies that have examined acquisition
outcomes in the past thirty years (e.g. Agrawal & Jaffe 2000; Datta, Pinches & Narayanan 1992;
King et al. 2004; Sirower 1997), spin-in acquisitions were, on average, value-creating for the
acquiring firms. This finding has potent implications for both scholars and practitioners since it
represents the first large-scale, multi-year pool of acquisitions for which a pathway to systematic
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success has been identified. Central to spin-ins’ comparative advantage are the gains spin-ins
generate in organizing efficiency; which, as our findings demonstrate, translates into better post-
acquisition outcomes.
Implications for Scholars
Our line of inquiry offers enhancements to existing theory and insights for future studies.
Most research on acquisition outcomes has focused on identifying and explaining the extent to
which a target company’s business is related to that of the acquirer and how this comes to affect
M&A outcomes (Rumelt 1982; Hayward 2002). Our framework introduces the need to
conceptualize hybrid forms of CE that simultaneously incorporate the benefits associated with
moving disruptive innovations outside the firm (Benner & Tushman 2002; Christensen 1997;
Hunt & Ortiz-Hunt, 2018), while reducing the information asymmetries that have traditionally
plagued M&A efforts. Spin-ins were shown to offer superior performance by reconfiguring the
“us vs. them” assumptions that often bedevil post-acquisition integration (Yu, et al. 2005). Our
framework builds on a robust conceptualization of relational ties and offers a more nuanced
theoretical perspective on how the selection of acquisition type contributes to acquiring
innovation profitably or unprofitably. Through this, we provide greater precision in assessing the
impediments to successful M&A strategies, while improving the predictive value of acquisition
outcome models.
Our study also underscores the importance of developing better measures to test the
comparative impact of internal and external innovation efforts. The results of our analysis
suggest that there is fertile ground in developing more comprehensive organizational theories of
how and why some CE initiatives succeed and others do not, particularly in balancing the dual
objectives of firm renewal and efficient organizing. The examination of spin-ins offers a
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compelling tool to reimagine and reassess the conditions under which firms decide to pursue
internal versus external CE efforts, as well as the comparative success or failure in minimizing
disruptions to existing business lines. We also open the door for fresh questions about how and
why firms face post-acquisition integration challenges.
Scholars pursuing research streams in CE, M&A, and strategic human resource management
can leverage and extend our explanatory framework by exploiting the far longer performance
horizons we have used in this study versus prior empirical work on corporate acquisitions. Since
acquisition-related performance unfolds over many years during which acquiring firms attempt
to develop profitable synergies, we took significant steps in designing our study to employ long-
term measures of acquisition performance. In particular, our study demonstrates the efficacy of
AAI as a robust measure of synergies (or lack thereof) across a time horizon that is far longer
than previous studies of corporate acquisitions. AAI provides a more accurate measure and a
more reliable evidence of long-term performance. Although the development of datasets using
AAI is costly and time-consuming, our results suggest that there are multiple theoretical and
empirical justifications for such an investment.
Implications for Practitioners
Our findings also stake out new strategic ground that is relevant to managers tasked with
leading innovation efforts through acquisition-driven CE. Spin-ins are far from being a “silver
bullet,” but they offer a number of fascinating prospects. Many industries are moving toward
increasing levels of open innovation, searching for new technologies outside the boundaries of
the firm, particularly in industries with high velocity technological change (Eisenhardt 1989).
Absent the prior ties we highlight in this study, there is ample reason to be skeptical regarding
the value-creating potential of acquisitions despite their popularity. In marked contrast, our
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hybrid framework stemming from the spin-out and spin-in model illustrates how acquisitions
with prior ties enable firms to retain scarce talent, while minimizing the common pitfalls of CE
pursued through corporate acquisitions. This also sheds new light on the crucial challenges of
post-acquisition integration. The findings indicate that acquirers need to take a broader view of
the interaction between ex-employees and current employees than extant frameworks have
contemplated (Birkinshaw et al. 2000).
Beneficial facets of spin-ins may be amplified with even greater attention to the reintegration
process. While spin-ins result in significantly better acquisition-related outcomes than non-spin-
in acquisitions, their efficacy as a component of any firm’s corporate entrepreneurship strategy
may be bounded by the acquirer’s ability to handle organizational and cultural disruptions that
stem from social cognition, particularly involving the reunification of innovative ex-employees
and those who remained with the parent.
The M&A performance short-falls caused by integration challenges have long been noted in
the literature (Birkinshaw et al. 2000; Graebner 2004; Nahavandi & Malekzadeh 1988; Vaara
2003). Superior acquisition performance has been found to occur only if synergies can be gained
through effective post-acquisition integration (Larsson & Finkelstein 1999), by properly
accounting for the crucial role of human capital in integration (Birkinshaw et al. 2000;
Cartwright & Cooper 1990). Consistent with these arguments, our study confirms that spin-ins
attenuate the value-destruction associated with information asymmetries, CEO overconfidence,
and post-acquisition integration. In the end, spin-ins appear to offer a lower risk, higher return
formula for the acquisition of innovation through market-based, external corporate venturing.
Limitations and Opportunities
!
36!
As with all studies, design decisions attendant to our investigation involved tradeoffs that
result in limitations, boundary conditions and opportunities for future research. The first
concerns the focus on software, electronics and high-tech manufacturing firms. The use of these
knowledge-intensive industries is consistent with related research (i.e., Agarwal et al., 2004;
Townsend, Hunt, McMullen & Sarasvathy, 2018) and was apropos to our research question,
which necessitated industries where innovation plays an important role and where there exists a
sizable population for a match-pair design (Hunt, 2013a). However, other sectors may not
display the same large effect size we found in our study; and, in fact, may not even have a
significant occurrence of spin-ins. Although our study makes no claims regarding the overall rate
of spin-in occurrence, they represented approximately ten percent of our fully vetted transaction
pool. This should be taken as a conservative, minimum value since it is possible that other spin-
ins occurred that we were unable to verify. Other sectors are unlikely to have a considerably
higher spin-in rate, given the innovation-oriented rationale for spin-ins, but many may have a far
lower rate. In either case, spin-ins are an important type of acquisition that merits additional
future research to examine inter-industry comparisons.
Additionally, we limited our purview to acquisitions ranging from $10 million to $150
million, comprised only of those undertaken by publicly traded firms. While this range captures
the great preponderance of all deals, smaller and larger transactions may reveal results that are
more or less extreme than those that emerged from our sample. Regarding prior ties,
considerable effort enabled us to identify a sizable population of firms fitting our definition of
“prior ties” as being ex-employees. There are, however, other important forms of prior ties,
stemming from partnerships, alliances, and contracting agreements that could have the same
effect as employment, educational and industry ties.
!
37!
Conclusion
In this study, we have proposed a framework wherein spin-ins constitute a hybrid approach to
acquisition-driven CE strategic aims. Traditional modes of pursuing CE through corporate
acquisitions are highly susceptible to the adverse effects of information asymmetries, CEO
hubris, and impediments to effective post-acquisition integration. This, in turn, leads to
expensive failures and chilling effect on much-needed CE initiatives among large-scale firms.
Conversely, hybrid approaches and novel organizational forms, such as spin-ins appear to
attenuate acquisition pitfalls by fundamentally rethinking how innovation can be acquired
externally without the unwanted baggage that leads to the value-destroying facets of the M&A
Paradox. In this respect, the use of spin-ins supports the increasing recognition and mounting
evidence that novel organizational forms, creative alliances, and boundary-spanning consortia,
may more aptly characterize the emergent nature of corporate entrepreneurial growth initiatives
than traditional conceptions of acquisition-driven CE.
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Table 1- Pairwise Matching
Table 2- Bivariate Correlations
Table 3 – Asset Write-Offs (AAI) at 5 Years Post-Acquisition
Acquisition
Type
Cohort
Firms (N)
Average
Acquisition Size
Mean Write-Off as
% of Total Acquisition
Spin-In
450
$28MM
21%
Non-Spin-In
450
$30MM
45%
Table 5 – Marginal Means for Interaction Terms by Level
Variable
Level
Mean Probability of AAI
Difference
Std.
Error
t-test
Spin-Ins
Non-Spin-Ins
Acquisition Type (AT)
N/A
0.45
0.73
0.28
0.0036
-77.99
AT x IA
Low IA
0.22
0.41
0.19
0.0018
-104.7
Mod IA
0.35
0.67
0.32
0.0048
-67.21
High IA
0.66
0.79
0.13
0.0100
-13.04
AT * CEO
Low CEO
0.21
0.37
0.16
0.0018
-87.64
Mod CEO
0.32
0.61
0.29
0.0044
-65.96
High CEO
0.62
0.86
0.24
0.0093
-25.78
AT * PAI
Low PAI
0.51
0.65
0.14
0.0029
-47.57
High PAI
0.39
0.84
0.45
0.0088
-50.95
Mean Std Dev
(1)
(2) (3) (4) (5) (6) (7) (8) (9) (10)
1Asset Impairment 0.47 0.36
2Acquisition Type (Spin-In = 1) 0.50 0.16 -0.24
3Acquiring Firm Size (Assets $ Bln) 15.83 11.42 0.03 0.08
4Busi Focus (Conglomeration = 1) 0.12 0.07 -0.02 0.10 0.13
5Prior Acquis Experience (Acquirer) 0.37 0.14 0.11 0.11 0.17 0.13
6NAICS Code Distance 0.22 0.08 -0.06 -0.05 -0.02 0.10 0.4
7Acquis Payment Method (Equity = 1) 0.67 0.24 -0.17 -0.07 0.01 0.06 0.09 0.02
8Intangible Assets as a % of Total Deal 0.72 0.21 -0.17 -0.03 0.00 0.04 -0.10 0.01 0.22
9Information Symmetry 3.40 0.87 0.15 0.24 0.09 0.06 0.03 -0.03 -0.10 -0.04
10 CEO Hubris 0.55 0.19 -0.19 -0.15 0.08 0.12 0.11 0.12 0.14 0.22 -0.09
11 Integration (fully integrated = 1) 0.68 0.18 0.11 0.08 0.04 -0.07 0.08 -0.16 0.02 0.07 0.17 0.05
Italics indicate correlation with p < .01. N = 900
Spin-Ins Non-Spin-Ins T-test P Value
Acquirer Size ($ bln) 15.6 15.9 0.40 0.69
Acquirer Age (yrs) 23.2 23 0.60 0.55
Target Age (yrs) 3.5 3.7 0.53 0.59
Transaction Amount ($) 28.4 28.2 0.33 0.74
Acquirer Prior Acquis Experience (# deals) 3.56 3.62 0.60 0.55
Business Industry Distance (NAICS codes) 312 308 0.92 0.36
Acquirer Busness Focus (% Conglomerate) 0.119 0.121 0.54 0.59
Payment Method (% Equity) 0.672 0.669 0.11 0.91
Intangible Assets as % of Acquisition 0.713 0.726 0.39 0.70
!
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Table 4 – Logistic Regression Results: Acquisition-related Asset Impairment (AAI)
Results of Maximum-Likelihood Logit Analysis for Impaired Assets
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Independent Variables
Macro-Economic Effects 0.10 0.11 0.10 0.09 0.09 0.07 0.10 0.06
(0.02) (0.02) (0.02) (0.02) (0.02) (0.01) (0.02) (0.01)
Industry Effects 0.14* 0.13* 0.14* -0.11 -0.09 -0.09 -0.08 -0.08
(0.04) (0.04) (0.03) (0.03) (0.03) (0.02) (0.02) (0.02)
Firm Effects 0.24* 0.18* 0.20* 0.17* 0.13* 0.11 0.12* 0.09
(0.07) (0.06) (0.05) (0.05) (0.04) (0.05) (0.04) (0.02)
Acquiring Firm Size - Assets 0.14* 0.12* 0.12* 0.12* 0.11 0.10 0.11 0.09
(0.04) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03) (0.03)
Busi Focus (Conglomeration = 1) 0.18* 0.15* 0.15* 0.15* 0.15* 0.15* 0.15* 0.12
(0.08) (0.06) (0.06) (0.06) (0.06) (0.06) (0.06) (0.04)
Prior Acquis Experience (Acquirer) -0.52*** -0.38*** -0.41*** -0.34** -0.18* -0.13* -0.17* -0.14
(0.20) (0.15) (0.16) (0.13) (0.11) (0.5) (0.11) (0.05)
Acquiring Firm Age 0.07 0.03 0.04 0.01 0.02 -0.01 -0.01 -0.02
(0.02) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)
NAICS Code Distance 0.24* 0.27* 0.19* 0.14* 0.08 0.08 0.08 0.05
(0.07) (0.07) (0.05) (0.04) (0.04) (0.04) (0.04) (0.02)
Acquisition Payment Method 0.83*** 0.65*** 0.70*** 0.53*** 0.31** 0.38** 0.29** 0.23*
(0.32) (0.23) (0.25) (0.18) (0.12) (0.18) (0.12) (0.08)
Intangible Assets as a % of Total Deal 1.17*** 0.94*** 1.03*** 0.88*** 0.52*** 0.43** 0.61*** 0.38**
(0.56) (0.40) (0.44) (0.37) (0.21) (0.21) (0.30) (0.18)
Target Firm Age -0.13* -0.07 -0.09 -0.07 -0.06 -0.05 -0.06 -0.05
(0.03) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
Acquisition Type (H1) -0.87*** -0.92*** -0.62*** -0.79*** -0.88*** -0.55***
(0.43) (0.48) (0.24.) (0.30) (0.31) (0.23)
Information Asymmetry 1.09*** 0.84*** 0.51*** 0.64*** 0.76*** 0.43**
(0.37) (0.28) (0.17) (0.23) (0.24) (0.15)
CEO Hubris 1.14*** 0.93*** 0.86*** 0.49** 0.78*** 0.31**
(0.50) (0.39) (0.33) (0.18) (0.26) (0.18)
Post-Acquisiion Integration 1.27*** 0.90*** 0.74*** 0.88*** 0.35** 0.34**
(0.42) (0.22) (0.17) (0.26) (0.14) (0.13)
Acquis Type*Info Symmetry (H2) -0.78*** -0.58***
(0.24) (0.17)
Acquis Type*CEO Hubris (H3) -0.82*** -0.49***
(0.29) (0.18)
Acquis Type*Integration Process (H4) -0.52** -0.28*
(0.21) (0.12)
Constant 1.78*** 1.55*** 0.96*** 1.29*** 1.17*** 1.38*** 1.15*** 1.36***
(0.74) (0.62) (0.41) (0.58) (0.49) (0.63) (0.51) (0.45)
Log Likelihood 419.2 517.2 484.0 594.9 603.8 585.9 638.1 617.4
c
2
207.7 335.2 304.1 418.5 512.3 447.6 402.7 562.3
Generalized R
2 (McFadden)
0.264 0.369 0.291 0.474 0.502 0.493 0.548 0.560
Predictive Accuracy 56.8% 72.6% 63.4% 82.0% 85.1% 81.7% 85.3% 89.2%
N = 900
Italicized values are standard deviations
***p < .001; **p < .01; *p < .05
Likelihood of Acquirer Recognizing Acquisition-Related Impaired Assets
!
46!
Figure 1 – Acquisition Type-Information Asymmetry Interaction (95% Conf. Intervals)
Figure 2 – Acquisition Type-CEO Hubris Interaction (95% Conf. Intervals)
Figure 3 – Acquisition Type-Post-Acquisition Integration Interaction (95% Conf. Intervals)
0
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0.4
0.5
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12345678910 11+
Probability of Write-Down
Years of Prior Association
Spin-Ins
Non-Spin-ins
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
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1
Probability of Write-Down
CEO Hu bris
Spin-Ins
Non-Spin-ins
Low High
!
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0
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0.3
0.4
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Low/Integration/ High/Integration
Probability of Write-Down
Post-Acquisi tion Integration
Spin-In s
Non-Spin-in s
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