Chapter 2. Literature Review
2.2. Outsourcing Innovation
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CARs in tender offers can be attributed to signaling effect of acquirers’ confidence as
well as discipline of targets’ management. And better performance in cash
transactions follows Myers and Majluf’s(1984) work, suggesting firms prefer to pay
cash as their stock is undervalued. Paying in Cash also signals higher capacity for
leverage and better ability to complete debt services in that cash payments are
commonly accompanied with debt financing. Tim and Anand also study return on
target firms and the result is consistent with those of prior studies- targets’ CARs are
on average positive. Additionally, the paper analyzes impact of acquirers’ size relative
to that of targets on their CAR performance of target firms, reaching a conclusion that
CARs decrease as the relative ratio of target over acquirer increase.
2.2. Outsourcing Innovation
There are several explanations for reasons why companies engage in M&A
activities. Motives to takeover activities typically include synergies, achieving growth,
enhancing market power, accessing uncommon capacities, boosting EPS and
diversification. Various inducements are broadly discussed both empirically and in
real business. The majority of prior studies points to operational and financial
synergies created as corporate entities combine. Erik, Palani-Rajan, and
Srinivasan(2009) suggest that operating synergies result from changes in operation,
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and financial synergies are mainly generated by tax savings and utilization of leverage.
In my article, I focus on operating synergies, particular on those due to innovation.
Recently, technological innovation has been mentioned as one of the reasons for
corporate takeovers. Chesbrough (2003) point out the “open innovation” business
model, instead of developing internally, the concept emphasize on outward-oriented
innovation network. In particular, companies are capable to achieve flexibility and
efficiency by accessing and exploiting knowledge outside the firms. This implies
technological innovations are eligible for one of the reason for M&As. Several studies
also investigate the impact of M&A deals on innovation performance. Hall (2006)
researches relation between acquisition and change in R&D intensity subsequent to
M&A, indicating a negative correlation, but the result is insignificant. In contrast, Hitt
et al. (1991) shed lights on both R&D as innovation inputs and patents as output.
They suggest trade-off exists between M&A investment- which is more predictable-
and risky R&D investment. Moreover, the outputs decline after acquisition as a result
of management unwillingness to champion ideas that leads to patent outcomes. The
significance becomes more apparent when it comes to diversifying acquisitions.
With regard to outsourcing innovation, Hagedoorn and Duysters (2002)
investigate the acquisition of technological capacities with the focus on high-tech
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industry- the computer sector. They stress on the significance of strategic and
organizational fit (relatedness) on innovation performance in computer industry, in
which the technological capacities are the critical sources of corporate
competitiveness. They also point out that influences of M&A on innovation may be
either short-term or long-term. As acquirers intent only to access existing R&D
capacities or technological output, the improvement in innovation capacity tend to be
temporary. On the other hand, M&As oriented from synergetic new process- or
product-related technologies eventually lead to long-term improvement in economic
performances as acquirers extend their technological skills and learning capacities
after M&As take place. Higgins and Rodriguez (2006) center their studies on
pharmaceutical industry, in which patent protection are the core of business. They find
firms suffering from deficiency in innovativeness are more likely to resort to
acquisition as a mean to outsource capacity in innovation. However, their works are
limited in particular R&D intensive industries rather than broad studies that we are
interested in.
Hitt et al. use patent counts as a measure of innovation output. However, patent
counts stand for innovation quantity, and “quality” may be ignored. Zhao (2009)
resolve these questions by using patent citation counts as the proxy for innovation
output quality and encompassing various industries over different time horizon. With
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this approach, Zhao studied the interaction between M&A transactions and innovation
capacity of firms involved in M&As. As acquiring innovation is less urgent for more
innovative firms, they are less likely to make M&A bids. And even when launching
into a takeover transaction, they are also less likely to complete the deal.
He further concluded that firms deficient in internal innovation effort resort to
external M&A market for gaining knowledge base in technological innovation. On
this premise, his work also shows formerly less innovative firms that complete the
bids enjoy the most positive CARs after deal completion, suggesting this group of
bidders benefit more than the contrasting group. In other words, buying innovation
is one of the major considerations in corporate takeover decisions, and most
importantly, it works!
Zhao’s work implies that acquirers are typically deficient in innovation capacity.
However, Bena and Li (2011) consider both innovation input and output (and
concerning both quantity and quality), yielding a somewhat different result. They
show that successful innovators as measured by patent outputs are more likely to be
acquirers, while targets are generally active in R&D investments but not as successful
as transferring innovation inputs into patents as acquirers. Furthermore, they also
work on technological relatedness between acquirers and targets, concluding that
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technological overlap contributes positively (and significantly) to merger pairing, and
is the critical source of synergy for M&A activities.
The remainder of my paper proceeds as follows. Chapter 3 describes the
methodology employed in this study. In addition, I will further describe the data
sources, variables selection and processing details. And then Chapter 4 presents the
empirical results. It includes both long-term and short-term studies, and the result of
calendar time portfolio. Last but not least, I will reach the conclusion in Chapter 5.
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