SUSTAINABILITY OF PATENT-BASED … of Patent-based Competitive Advantage 3 Sustainability of...

Sustainability of Patent-based Competitive Advantage 1

SUSTAINABILITY OF PATENT-BASED COMPETITIVE ADVANTAGE

by

Kathryn Rudie Harrigan

Henry R. Kravis Professor of Business Leadership

Columbia University, 701 Uris Hall, New York, NY 10027 USA, 001-212-854-3494,

[email protected] [corresponding author]

Maria Chiara DiGuardo

Associate Professor

University of Cagliari, Viale Fra Ignazio 74 – 09123, Cagliari, Italy, 039- 0706753360, [email protected]

Research assistance was provided by Jesse Garrett, Donggi Ahn, Hongyu Chen, Elona Marku-Gjoka, the Patent Office of the Sardegna Ricerche Scientific Park and Thomson Reuters.

mailto:[email protected]

mailto:[email protected]


Sustainability of Patent-based Competitive Advantage

Abstract

Patents have been touted as being the type of resource which provides a basis for longer-lived

competitive advantage, but as the pace of technological change accelerates, even patents have

become questionable sources of sustainable competitive advantage. In settings where no

sources of competitive advantage are sustainable for long (and no resources convey advantage

forever), managers have sought temporary respite in resources, in how managers organize and

coordinate their operating activities and routines, in recruiting superior knowledge workers,

developing keener learning capabilities and absorptive capacity, and in learning how to copy

competitors’ sources of competitive advantage more nimbly. We find that the duration of pa-

tent-based sources of competitive advantage is limited, but that duration is longer where firms

have patented inventions that incorporate a broader range of technological knowledge that is

not core to the grants described in their respective patent applications.


Sustainability of Patent-based Competitive Advantage Introduction

Competition is like being on a treadmill (also likened to the Red Queen effect) in the sense that

firms must continually renew themselves through various types of innovative activities in order

to keep up with other firms’ newest competitive sorties (D’Aveni, 1994; Teece, et al., 1997). The

unique and inimitable resources and capabilities which give the incumbent firm temporary pro-

tection from losing customers’ patronage are the basis of that firm’s competitive advantage

and the duration of its protected status from rivals’ imitation refers to the sustainability of said

advantage.

Imitation is the most likely means for competitors to try to steal away customers; new

entrants may even be successful at doing so unless the incumbent firm possesses some basis

for serving customers that is especially difficult for competitors to emulate (Bain, 1956; Peteraf,

1993; Porter, 1980; Wernerfeldt, 1995). As an industry’s structure evolves, competition therein

becomes a fight against the eternal price-cost squeeze of cutthroat rivalry and diminished

product differentiation which destroys firms’ distinctiveness (Porter, 1980; 1991). As firms

push back against the profit-eroding forces of competition, they seek to acquire (or develop)

new sources of competitive advantage that will either preserve customers’ willingness to pay or

improve firms’ abilities to take expenses out of their internal cost structures. In this process,

firms’ competitive struggles seem, at best, to provide only temporary respite against incursions

by increasingly-aggressive adversaries who can recombine their innovative resources and ideas

creatively to win the patronage of customers whose loyalty is fickle (Bettis and Hitt, 1995;

D’Aveni, et al., 2010).


As their industries trudge inexorably towards competitive stalemate, managers inside

these beleaguered firms hunt for some temporary respite against creative destruction (Schum-

peter, 1942) and disruptive competitive changes (Christensen, 1997). Their basis for serving

customers effectively evolves continually from gaining advantages that may reside in resources

(Bain, 1956; Barney, 1991; Dierickx and Kool, 1989; Peteraf, 1993; Thomas, 1996; Wernerfeldt,

1995) to finding advantages in how managers organize and coordinate their operating activities

and routines (Porter, 1996; Powell and DentMicallif, 1997) to advantages based on recruiting

superior knowledge workers (Drucker, 1999; Groysberg, et al., 2008; Harrigan and Dalmia,

1991) to developing keener learning capabilities and absorptive capacity (Arikan and McGahan,

2010; Cohen and Levinthal, 1990; Lane and Lubatkin, 1998; Lane, et al., 2006; Volberda, et al.,

2010) to making the firm’s organizational capabilities suitably dynamic so that its people can

copy competitors’ sources of competitive advantage more nimbly (Helfat and Peteraf, 2003)

because the duration of any single basis for competitive advantage seems to be brief. In many

industries, it seems that no sources of competitive advantage are sustainable for long and no

resources convey advantage forever (Collis, 1994; D’Aveni, et al., 2010; McGrath, 2013; Ruefli

and Wiggins, 2003).

Patents have been touted as being the type of resource which provides a basis for long-

er-lived competitive advantage (Reitzig, 2004; Sander and Block, 2011; Schankerman, 1998).

This hopeful outlook has endured, perhaps, because patents have granted a temporary mo-

nopoly on a particular use of knowledge as it was combined in firms’ useful inventions. As the

pace of technological change has accelerated, however, even patents have become questiona-

ble sources of sustainable competitive advantage. Our contribution to the debate concerning


the duration of competitive advantage investigates whether patent-based advantages prove to

be the exception to a scenario where most investments in resources and capabilities offer di-

minishing returns. To do so, we contrast the operating profit margins of firms having patents

with those who do not, as well as test propositions concerning which types of patents offer

longer-duration competitive advantages. In order to investigate the duration of patent-based

competitive advantages, we also decompose the components of patent applications to distin-

guish which types of patents are most-difficult for competitors to emulate.

Theory and Hypotheses

Competitive advantage arises from the temporary amassing of resources and capabilities which

allow vendors to win customer patronage while also earning normal profits (or better). In 1994,

Collis posited a scenario in which entry barriers would become meaningless and the value of

resources, capabilities, organizational routines and other activities that had previously been

considered to be sources of advantage would be easily matched by substitute assets of equal

value. Tacit knowledge would no longer create relevant advantages in this scenario as competi-

tors learned that they need not copy the extant sources of firms’ advantage; they needed only

to imitate those product traits which customers valued as quickly as they were introduced by

their innovators. In such a world, Collis (1994) noted, there would be no sustainable competi-

tive advantage if competitors could quickly match any product-market proposition that cus-

tomers found valuable.

Collis’ (1994) scenario became plausible because many scholars found that superior per-

formers had difficulty in sustaining their performance levels over time if their distinctive value

proposition was easily imitated by rivals (D’Aveni, 1994; McGrath, 2001; Ruefli and Wiggins,


2003). In 2010, D’Aveni, et al. posited that Collis (1994)’s scenario of an environment with no

sustainable advantage represented a special case of industry structure―anticipating, as McGa-

han and Porter (1999) had concluded, that adverse changes within an industry’s structure

would have a more persistent negative impact on firm profitability than would changes in firms’

individual strategic outlays. Firms continued to invest in patentable inventions in the hope of

earning more-than-proportional returns for making R&D investments.

Not only have firms continued to invest in strategic resources (such as advertising and

R&D) without causal certainty that such activities would increase sales and profitability, firms

have also continued to modify their organizational routines in order to renew their competitive

capabilities in an effort to stay abreast of competitors (Barney, 1986; Novak and Stern, 2008;

2009; Nelson and Winter, 1982). Most firms have been oblivious to the risk that the value of

patents as a source of competitive advantage could become less enduring when the type of in-

novation needed to cope with competitive turmoil became more radical in nature or when their

scientific knowledge grew obsolete (Henderson, 1993). The durability of patent-based ad-

vantage, in particular, was at risk of becoming shorter-lived within industries that were charac-

terized by rapid and multi-faceted technological change (Tushman and Anderson, 1986).

Patent-based advantage

Technological innovations (such as patents) were thought to be a source of differentiation that

offered a more-enduring competitive advantage because some inventions’ attributes were truly

inimitable; although technological progress occurred often, the evolution of industry structure

fostered spurts of innovative activity (punctuated by disruptive years of discontinuous change)

and awarded temporary entry barriers to the victors in the form of patent-based competitive


advantage (Aghion, et al, 2005; Cohen and Levin, 1989; Kamien and Schwartz, 1974; Scherer,

1967; Schumpeter, 1942; Tirole, 1988).

Because high-quality patents earned rents through their royalties, the stock market val-

ued firms who had patents as though their patents were indeed valuable (Bessen, 2008; Bos-

worth and Rogers, 2001; Cockburn and Griliches, 1988; Griliches, 1981; Hall, et al., 2005; Lan-

jouw, 1998; McGahan and Silverman, 2006; Villalonga, 2004), even though only a small propor-

tion of all patents actually captured large returns from their royalties (as was indicated by the

proportion of forward citations that they garnered) and those inventions were constantly at risk

against competitors who might create innovations which surpassed them (Harhoff, et al., 1999;

Lanjouw, et al., 1998; Scherer and Harhoff, 2000).

As a prerequisite of being granted, patents must be published and knowledge of the in-

vention then becomes disseminated (Johnson and Popp, 2003). Some firms do not want to pa-

tent their inventions for this reason; others do not want their patents to be subsequently cited

by others―lest knowledge of their patent’s content inspire others to invent their way around a

device that may be protected by a thicket of patents (Bessen and Meurer, 2008; Zamocin,

2013). Either way, firms invest in R&D and act as though they believe that their patents are

valuable.

R&D and patents

Competitive benefits from patenting are often examined jointly with the positive effects

of making R&D outlays (Artz, et al., 2010; Cohen, et al., 2013; Gambardella, 1992; Hall, et al.,

2005; Hedge and Sampat, 2009; Jaffe, et al., 2000; Kelley, et al., 2013; Mazzucato and Tancioni,

2012). The causal relationship between R&D outlays and benefits from patents has sometimes


been difficult to isolate―due, in part, to uncertainty concerning the appropriate lags to consid-

er when linking R&D outlays to the granting of patents. Because most previous studies that

have linked patent value to R&D outlays have depended primarily on patent counts and analy-

sis of patents’ patterns of forward citations (Belezon, 2011; Breitzman and Thomas, 2002; Chen,

et al., 2010; Hall, et al., 2001; Jaffe, et al., 1998; Lee, et al. 2007; Patel and Ward, 2011; Silver-

berg and Verspagen, 2007; Trajtenberg, 1990), we know that the time period between making

R&D expenditures, receiving a patent, and garnering a substantial record of citations can be ex-

tensive. Forward-citation counts have long been used as a proxy for patent value, but tests of

whether having patents makes firms more profitable than those competitors having no patents

are less abundant (and may be of interest when investigating the strength of patents as an en-

during source of competitive advantage). Similarly, tests of patent content have not yet indicat-

ed patterns that may be linked with firm profitability. Our tests of patent content use infor-

mation about backward citations (instead of the more-common forward citation estimates of

value) to assess how patents create competitive advantage.

Competitive environments that support competing technological routes (or standards)

may be especially likely to erode the viability of patent-based advantage, shorten the duration

of such advantage, or negate its strength as a competitive advantage altogether―especially

where there is greater risk of obsolescence should a firm invest in that technological route

which does not ultimately become the industry standard. Some patents may lose their viability

as a competitive advantage within turbulent settings where the chain of value created by path

dependency has been broken by the frequent discontinuities caused by technological disrup-

tion (Arikan and McGahan, 2010; Schreyögg and Kliesch-Eberl, 2007).


Patents in communications services

Communications services is an industry that has been subject to the type of creative destruc-

tion described by Schumpeter (1912) in which multiplexing technology multiplied the carrying

capacity of bandwidth to accommodate data and video as well as voice traffic―making simple

bandwidth investments obsolete. Some communications firms have invested heavily in re-

search and development because they presumed that the inventions which they patented

would provide them with competitive resources which could be exploited temporarily to give

them superior profitability (Gambardella, et al., 2008; Jaffe, 1986). Other firms within the same

industry have become fast followers who copied those aspects of innovations which customers

seemed to favor. Ironically, enabling technology became readily available to the fast followers

as inventors licensed the use of their patents to recover rents as quickly as possible within their

own tumultuous industries.

We investigated the effects of having patents on acquiring firms who competed in the

communications services industry during the exuberant years of internet commercialization in

order to investigate the existence and sustainability of patent-based sources of competitive ad-

vantage. Our research design was longitudinal in its scope in order to ascertain the longer-term

impact of having patents on post-acquisition operating profit margins; acquiring firms were

used as a basis for comparison because acquisitions represent an overt effort to grow the firm

via corporate renewal. For some firms, acquisitions represent their best hope of survival within

industries characterized by frequent technological evolution—especially if their in-house

knowledge absorption has been inadequate to cope with their changing competitive environ-

ment.


We compared the performance over time of firms having patents with that of acquiring

firms without patents and expected to find differences in firms’ profitability over time. We test-

ed for absolute differences in profitability as well as for the duration of the expected contrast in

profitability between firms who had patents versus those who did not.

Hypothesis 1a: Firms having patents will enjoy higher return-on-sales ratios than do competi-

tors within the same industry who do not have patents.

Hypothesis 1b: Firms having patents will enjoy higher return-on-sales ratios for a longer peri-

od of time than do competitors within the same industry who do not have pa-

tents.

Patents which convey sustainable competitive advantage

McGahan and Porter (1999) argued that important structural changes within an industry (e.g.,

entry, exit or effective imitation by extant competitors) drove profit levels over time to the in-

dustry’s mean―except in the case of firms possessing inimitable resources. Our second set of

hypotheses test for evidence of such an exception, i.e., firms possessing patent assets which are

more difficult for competitors to imitate are expected to extend the duration of competitive

advantage. Our method for testing these hypotheses decomposes firms’ patents into their core

and non-core knowledge antecedents.

When patents are granted, a coding system is used to describe the particular technolog-

ical areas which were combined to create the invention. The coding system also indicates the

technological areas of backward-cited patents that are listed as intellectual precedents of the

patent whose claims are being examined.1 If researchers combine their firm’s routine techno-

1 The coding system could be that of the United States Patent and Trademark Office codes (USPTO), the World Intellectual Property Organization’s International Patent Classification codes (IPC), the jointly-sponsored Co-


logical knowledge with external knowledge flows that are unusual and non-routine for them,

they may create new technologies (Henderson, 1993; Kim, et al, 2012; March, 1991; Sorensen

& Stuart, 2000), improve their innovative outcomes (Escribano, et al, 2009; Lane, et al, 2006;

Volberda, et al, 2010), accelerate competitive response times, and institutionalize the ability to

make radical innovations when needed (Ahuja and Katila, 2001; Cloodt, et al, 2006; Noote-

boom, et al, 2007; Tsai, 2009). Depending upon the extent of inventors’ exposure to distant

technologies and the nature of their investigative processes, firms may develop an in-house ca-

pacity for synthesizing distant technologies in their subsequent inventions (Cohen & Levinthal,

1990) or they may acquire expertise for integrating such knowledge from acquisitions. Regard-

less of how inventors gained exposure to novel technology streams and the ability to assimilate

such knowledge into their patents, we expect that having the ability to create radical techno-

logical combinations will be a source of advantage that would be more difficult for imitators to

emulate easily.

An innovation is radical in the sense that it requires inventors to process quite different

kinds of information (Henderson, 1993). Periods of radical technological change―like that

which the commercialization of the Internet represented―may have fostered the need for

greater radical innovative content to realize the Internet’s potential. In such environments, the

technological precedents that will be cited in firms’ patents may reflect the types of greater

stretches in knowledge that must be mastered to cope with such developments; these types of

inventions are similar, in spirit, to radical innovations because inventors must widen their

search range beyond their traditional comfort level to reach their scientific solutions (Dahlin

operative Patent Classification codes (CPC), or Thomson Reuters’ Derwent World Innovation Index codes (DWII), among others.


and Behrens, 2005; Garcia and Calatone, 2002; Green, et al., 1995; Henderson, 1993;

Schoenmakers and Duysters, 2010). Patents which stretch the limits of organizational

knowledge in this manner are risky (because such inventions may not be adopted as industry

standards), but they offer a better probability of extending the duration of competitive ad-

vantage than do innovations which merely replicate extant knowledge and capabilities in mak-

ing incrementally-novel inventions (Lin, et al, 2012; Makri, et al, 2010; Rosenkopf & Nerkar,

2001).

Audia, et al. (2000) noted that successful firms often wish to perpetuate the basis of

their past successes―even when environmental change calls for the creation of new competi-

tive resources―which is why new entrants (or smaller firms who have been acquired by incum-

bents) are expected to be the greater risk takers (who will engage in broader search activities to

formulate novel solutions to customers’ problems). Regardless of how firms became capable of

forging discontinuous technological innovations, we expect that those firms who can incorpo-

rate greater proportions of exotic, non-core knowledge into their inventions will enjoy competi-

tive advantage of longer duration―if their out-of-the-box inventions are successful at all.

Hypothesis 2a: Firms awarded patents with higher proportions of non-routine, non-core

knowledge synthesized with in them will enjoy higher return-on-sales ratios

than do competitors who do not have patents reflecting such radical inventions.

Hypothesis 2b: Firms awarded patents with higher proportions of non-routine, non-core

knowledge synthesized with in them will enjoy higher return-on-sales ratios for

a longer period of time than do competitors within the same industry who do

not have patents reflecting such radical inventions.


In summary, if patent assets prove not to be as unique and durable as sources of com-

petitive advantage as was hoped for, it may be because of technological obsolescence and rapid

dissemination of knowledge (or because inventors do not stretch themselves dramatically

enough in their search for ideas). In such settings, researchers would be continually searching

for new knowledge that might be integrated with their ongoing technologies to synthesize truly

unique inventions. If patent-based sources of competitive advantage are perceived to be at risk,

firms’ routines would evolve to include searches for novel uses of knowledge, greater experi-

mentation, more flexibility and frequent risk-taking activities as would be needed for firms to

become the type of moving targets whose advantages will be more difficult for competitors to

emulate (McGrath, 2001). The inventions issuing from such exploratory search activity would

be distinctive because their backward-citation patterns would differ greatly from extant patents

that may have relied extensively on building upon firms’ familiar technological areas; such

knowledge may be radically different from core areas of expertise where the firm has patented

extensively in the past. These types of inventions are radical because they have the potential to

propel industry evolution and promote synergistic technological progress (Gambardella and

Torrisi, 1998; Malerba, 2006; Mowery and Rosenberg, 1998; Nelson and Winter, 1982). Expo-

sure to outsiders’ ideas will also exacerbate the pace of technological change―as has occurred

in many industries where specialist firms have shared knowledge through their strategic alli-

ances (Harrigan, 1985) or in other arrangements that accelerated the diffusion of knowledge.

Methodology

Our tests of the sustainability of patent-based competitive advantage used post-acquisition

analyses of the operating margins of firms who acquired targets in the communications services


industry between 1998 and 2005. For parallelism, the performance of acquiring firms with and

without patents are compared. We track the post-acquisition profitability of their recovery

years (after integrating their acquisitions) and beyond―using the acquisition year as a common

benchmark for comparison.

Although it appeared to be a highly-attractive industry―due to its rapidly-growing de-

mand and the spectacular stock market valuations of firms operating therein―the communica-

tions services industry lost its luster when firms’ capacity expansions outran the demand of cus-

tomer firms to absorb it; the average operating margins of telecommunications carriers were

low – especially for the newer-technology lines of business. Rapid rates of technological obso-

lescence shortened the recovery time available for some communications firms to justify their

capital expenditures as multiple technological modes competed to carry voice, data and video

content during this era. A competitive shake-out was inevitable.

Acquisitions included in sample

Our window of analysis―U.S. firms’ operating margins from 1998 through 2012 (depending

upon when a particular acquisition was consummated and integrated with ongoing opera-

tions)―included a period of rapid industry growth from 1998 through 2005 when overall com-

munications revenues grew by 60% (by an average of 8.5% per year). Within this growth trend,

some communications products faced declining demand while other products thrived. For ex-

ample, revenues (and profits) from wireless telecommunications services surpassed revenues

from wireline services during 2008 and thereafter (Bureau of Census, 2014); industrywide reve-

nues for wireline communications services actually began declining as early as 2000 (Bureau of

Census, 2014). Some firms entered the communications industry by pricing services below their


fully-allocated costs in an effort to buy market share; other firms reported negative operating

margins because they spent heavily on research and development to produce patentable inven-

tions (or incurred acquisition premiums which they could not amortize in a timely fashion).

Thomson One’s Mergers & Acquisitions database (2013) reported that (between 1998

and 2005) 2,028 acquisitions were made of target firms which provided wired telecommunica-

tions (landlines) in NAICS 517110, wireless telecommunications (composed of cellular and/ or

paging services) in NAICS 517210, satellite telecommunications in NAICS 517410 (and resellers

of trunk line capacity in NAICS 517911), cable and other program distribution services in NAICS

515210, and/ or other communications services in NAICS 517919.2 Some firms also provided

broadcast (NAICS 515120), media (NAICS 512110) or internet services (NAICS 519130) because

they were thusly-diversified when the acquisition of interest occurred. COMPUSTAT financial

data (2013) were available for 1,194 of those reported transactions. Because some acquiring

firms closed more than one communications services transaction in one or more of the years

that were included in our eight-year observation window, transaction details for each acquiring

firm were combined for each respective year to yield 606 usable observations representing 309

distinct firms and covering eight years of acquisition activities. Some firms made acquisitions in

multiple years and 360 of those observations involved firms who had patents. Our post-

acquisition patent scores included the combined patent outputs of acquiring and target firm;

pre-acquisition patent scores included the patents of acquiring firms only.

2 NAICS code 517919 included dial-up, online access to Internet, or VoIP service providers (using client-supplied telecommunications connections; earth stations (except satellite telecommunication carriers); satel-lite tracking stations; radar station operations; satellite telemetry operations and/ or telemetry and tracking system operations on a contract or fee basis.


--------------------------------------------- Exhibits 1a, 1b, 1c and 1d here

--------------------------------------------- Financial variables

Exhibit 1 describes the variables used in testing our hypotheses; we present means and correla-

tions for the sample with and without patents. Our dependent variable, Return on sales (ROS),

was calculated by dividing earnings before interest, taxes, depreciation and amortization

(EBITDA) by revenues; ROS is also called the firm’s operating margin percentage because it indi-

cates profitability from operations (before financing charges and allowances for future capital

expenditures were deducted). In undiversified firms, return on sales ratios would indicate their

profitability within a specific industry. Our use of the operating margin percentage as a per-

formance measure captured the relative profitability of those firms that acquired one (or more)

communications services firms during the years of 1998 through 2005. We tracked their post-

acquisition operating margin percentages for as many as ten years after their transaction was

consummated and interpreted their ROS ratios as indications of the relative post-acquisition

profitability of their respective strategic postures. As acquiring firms were themselves acquired

(or went bankrupt), the number of observations per year thereafter declined until the depend-

ent variable eventually reflected only the strong performance of surviving firms.

During the years of 1998 through 2005, the communications services industry was char-

acterized by aggressive competitive behaviors (that adversely affected operating margin per-

centages) and the use of optimistic accounting practices whereby operating losses sometimes

exceeded firms’ sales volumes. These losses occurred as communications firms expended funds

in anticipation of demand for their product offerings during a bubble period when firms felt

great urgency to capture market share. Such optimistic “Internet accounting” policies extend-


ed, in particular, to high levels of research and development (R&D) expenditures as numerous

firms invested heavily in competing innovations without evidence of their commercial poten-

tial. On average, R&D expenditures per sales were higher in the four years immediately after an

acquisition was made than they were in subsequent years―indicating a spurt in research and

development outlays which may have included some of the costs of integrating acquired re-

search facilities. Return on sales ratios were typically lower in the first years after an acquisition

occurred―which may reflect the additional R&D outlays expended to create inventions from

unusual knowledge antecedents. Because research expenditures may impair short-term profit-

ability (but ultimately yield patents which convey competitive advantage), R&D variables were

lagged in our model specifications for testing the effects of having patents.

--------------------- Figure 1 here

---------------------- The year of each consummated transaction was coded as ROS0 to track its respective,

post-acquisition improvement in profitability over time. In the pooled sample of Figure 1, the

average return on assets performance of firms without patents is very similar to that of those

firms who had patents before making their acquisitions and continued to patent after their

transaction had closed. We note that only the subset of firms who acquired their patents via

acquisition (and had no patents prior to their transaction) enjoyed superior average return on

sales ratios over the post-acquisition time that we tracked.

--------------------- Figure 2 here

---------------------- Figure 2 reveals that―except for transactions consummated in 2003―average post-

acquisition return on sales ratios were highest for firms who acquired their patents via acquisi-


tion (and had no patents prior to their transaction). The year-by-year analysis indicates that av-

erage post-acquisition operating-margin percentages of firms without patents were similar to

those of firms with a history of patenting before and after consummating their transactions.

The visual evidence suggests that Hypotheses 1a and 1b cannot be accepted.

We tested post-acquisition return on sales ratios as dependent variables for several

years after an acquisition had been consummated and found that the average, incremental

post-acquisition improvements in return on sales changed their slope by the fourth year after

an acquisition was consummated. Indeed, Figure 1 shows that average operating-margin per-

centages converged by year5, regardless of whether the firm had patents or not. Average oper-

ating margin percentages increased more slowly after year4―suggesting that (on average) im-

provements enjoyed from integrating a particular acquisition were fully-realized by year4 and

something more was needed to push return on sales ratios higher.

Figure 2 examines average post-acquisition return on sales ratios by the year when the

transaction closed; it shows that average post-acquisition return on sales ratios tended to con-

verge over time for transactions that closed during the most-turbulent years of competition.

We had expected that the operating margin percentages of surviving firms would be higher if

they had patents, but Figure 2 suggests that only firms with newly-acquired patents were a sig-

nificant discriminator of ROS performance – especially after the industry’s competitive shake-

out in which 48 percent of acquiring firms were themselves acquired (or liquidated). Of particu-

lar interest is the poor performance of those “old-economy” firms who had patents before ac-

quiring in 1998 and 1999, but were not awarded patents subsequently. Their low average long-


term performance suggests that they were also on the road to bankruptcy (or acquisition) in

the years after 2008 (which is when our financial data for them ended).

Backward-citation patent scores

Our patent-scoring methodology created annual, aggregated scores for firms’ patents that were

constructed of “core” scores that characterized the technological areas in which the claims of

each respective patent were granted and “non-core” scores that characterized the antecedent,

“non-core” technology class codes that were different from those technology class codes that

were assigned to a particular patent. Each patent score was weighted by the frequency with

which particular dyads of technology class codes appeared together in patents granted in a par-

ticular year (relative to the frequency of all of the other possible dyads of technology class

codes for all patents granted in that respective year). A high score represented a synthesis of

technological precedents from a broad range of technological classification codes, while a low

score reflected that a patent’s backward citations came from a narrower array of technological

classification codes.

V-score as corrected total patent score

Because our patent-score methodology allowed for the inclusion of a large number of different

core (and non-core) technology class codes for each patent, the calculations were done in a

spreadsheet matrix that juxtaposed each core technology class code with itself and all other

technology class codes. Rows represented core- as well as non-core codes; columns represent-

ed the core technology class codes awarded to a particular patent. The weightings by which

counts of the frequency of each technology class code were adjusted used averaged probabili-

ties for each dyad of technology class codes occurring (modified annually for each patent


year).3 The backward-citation patent score, V, was equal to the Raw Innovation Score (the sum

of the core score and non-core score)―multiplied by a correction factor, [fo/fi], which was

the ratio of the count of outside-the-core technology class codes divided by the ratio of the

count of inside-the-core technology class codes:

V = ([ai,ao ffk]k) [fo/fi]

The correction factor decomposed the sum of all technology class codes according to whether

they were inside-the-core or outside-the-core. The factor score was a useful criterion for sort-

ing patents by their mix of content.

Raw score as core and non-core scores

The Raw Innovation Score, Wk, was the sum of all weighted scores for all technology class codes

appearing in a particular patent, ([ai,ao ffk]k), and it was also the sum of the core score and

non-core score―which means that each component of Wk could be investigated separately.

Using the convention that in represented n- different inside-the-core technology class codes

that may appear in a patent and om represented m- different outside-the-core technology class

codes that may have been cited by that patent, we calculated the average dyad weighting, ai or

ao, for each respective technology class code as:

ai = pj/in for inside the core (and ao = pj/om for outside the core)

where pj was the dyad weighting for a particular core (or non-core) technology class code ap-

pearing with itself or with another backward-cited technology class code and j equaled n times

(n + m). Each technology class code’s frequency factor, ffk, was calculated as:

3 The probabilities per dyad occurring were based on the actual probability for the patent’s earliest priority date―which was the year of the first USPTO filing related to the patent that was ultimately granted.


ffk = fk/F

where fk was the frequency with which a technology class code occurred in a particular patent

and F was the sum of all technology class codes appearing in that patent and k equals 1, 2, …, n,

n+1, …, n + m. The frequency factor was multiplied times the average dyad rating per technolo-

gy class code and summed according to whether the technology class code was inside-the-core

or outside-the-core in the patent award. The core and non-core scores were added together to

create the Raw Innovation Score―which was multiplied by the ratio of non-core to core tech-

nology class code counts.

Weighting the frequency of technology class codes.

The weightings by which the frequency of core and non-core technology class codes were

summed in our patent-score index used the actual annual frequency with which specific dyads

of technology class codes appeared (relative to all of the other possible dyads that could have

appeared together in a particular year). The matrix of interaction dyads formed a Reference Ta-

ble; the weightings in each year’s Reference Table were adjusted annually to reflect the near-

ness of technological confluence that was evolving as knowledge was diffused.

Our weighting of the frequency of technology class codes differed from Hall, et al.

(2001)’s operationalization of Trajtenberg, et al.’s (1997) backward-citation patent score in

three important ways. First, Hall, et al. (2001) assigned weightings based on the frequency with

which codes occurred. Second, they did not distinguish the effects of core from non-core tech-

nology class codes in calculating each patent’s score. Third, Hall, et al. (2001) did not adjust

their weightings of their index to reflect the rate of technological change occurring―which ac-

celerated over time within many industries, including communications services.


We used the technology coding system associated with the Derwent World Patents In-

dex (2013) to calculate our patent scores. The logic of our patent-scoring methodology is con-

sistent with the framework suggested by Trajtenberg, Henderson and Jaffe (1997)―which was

operationalized in Hall, Jaffe and Trajtenberg (2001)―but it utilized 289 technology class codes

for classification instead of their 36 classification codes (and counts of the occurrence of various

codes were weighted by frequency measures according to each respective year’s distribution of

all patents awarded to all firms―instead of using the Trajtenberg, et al (1997) system of

weighting when building our scores). The weighting by which the Raw Innovation Score was

multiplied gave emphasis to those patents which built upon novel technological class

codes―since those patents could represent a fruitful pattern of synthesizing knowledge from

diverse fields. A firm’s patent scores were aggregated on a year-by-year basis. Both 4-year and

7-year averages were also constructed by summing averaging the yearly patent scores accord-

ingly.

In using patent scores to represent firms’ sources of technological advantage, we ac-

cepted the cautions of Jaffe, et al., (2000) that lawyers and professional patent examiners add-

ed over two-thirds of the cited antecedents that were contained in firms’ patent applications

(Alcacer and Gittleman, 2006; Gittleman, 2008). We assumed that the various areas of techno-

logical knowledge which the backward citations indicated had been synthesized within a partic-

ular invention were appropriately cited―whether inventors themselves could identify the spe-

cific patented antecedents (or not). We inferred that inventors engaged in exploratory learning

to understand the novel technologies which they synthesized when patent scores were high;

we inferred that inventors relied on extant knowledge when their patent scores were low. We


expected that high patent scores would support higher return on sales ratios and that the dura-

tion of this particular source of competitive advantage would be greater than for less-complex

sources of advantage.

-------------------------------- Figures 3 and 4 here

-------------------------------- Figure 3 shows that for most years in the pooled sample, the highest average return on

sales ratios were enjoyed by acquiring firms with higher backward-citation patent scores. In

Figure 4, which examines operating margin percentages on a year-by-year basis (depending on

when a transaction closed), firms with high backward-citation patent scores enjoyed the high-

est average performance in half of the years examined. Firms having no patents had the high-

est average return on sales ratios in the four years when the competitive shakeout occurred in

communications services (which were the years 2000 through 2003).

Control variables

The logarithm of total assets is specified as a control variable in many models to test the effect

of firm size on return on sales because scale economies (and large market share) have long

been viewed as being important sources of competitive advantage; we were curious to know

whether size was harmful to strategic flexibility in such a turbulent competitive environment as

communications services and included it in our model specifications.

The effect of diversification was approximated by constructing a concentric NAICS-based

index that combined the distances of the acquiring firm’s lines of business (and those of the

target firm) from the NAICS code representing the combined firm’s primary line of business.

The effect of capital intensity was approximated using the ratio of total assets to number of

employees, and employee productivity was approximated by using the ratio of total revenues


to number of employees. R&D intensity was specified as the ratio of R&D expenses to sales and

R&D productivity was approximated as the number of annual patents awarded divided by R&D

expenses. Dummy variables were added to represent the combined firm’s presence in wired,

wireless, and internet services, among others. The line-of-business variables were not mutually

exclusive; many firms in our sample engaged in multiple lines of business simultaneously.

Results

Tests of patent-based effects over time on firms’ operating margin percentages suggested that

a strong and persistent relationship existed between return on sales ratios and those patent

scores which indicated higher novelty in the knowledge antecedents which patents built upon,

but the simple effect of having patents waned in significance in the years after an acquisition

was consummated. Not only did patent score variables have positively-signed and statistically-

significant coefficients in tests of post-acquisition returns on sales, but change variable analysis

showed particularly strong results in the return on sales performance of early years. Neverthe-

less results ultimately suggested that patent-based sources of competitive advantage were of

limited duration in their significance in both of our models of patent-based sources of competi-

tive advantage.

--------------------- Exhibit 2 here

---------------------- Effect of having patents

Six models tested the effects of having patents on the return on sales ratio for the first five (and

then seventh) post-acquisition years (which are coded as ROS1, ROS2, … ROS7, respectively). In

Exhibit 2, the sign of the having patents variable was positive and statistically-significant for the

first four years after an acquisition was consummated; the variable becomes negative thereaf-


ter―suggesting that patents are no longer an effective discriminator of return on sales perfor-

mance. Results suggested that the post-acquisition, incremental advantage on operating mar-

gins of simply having patents was not sustainable for long; more sources of advantage were

needed over time―a finding which was consistent with D’Aveni’s (1994) notion of hypercom-

petition and McGrath’s (2013) argument that competitive advantage is not sustainable.

In all six models tested in Exhibit 2, the signs of the research and development to sales

variables were negative and statistically-significant (which was not surprising since R&D ex-

penses were deducted from gross margin when computing the operating margin percentages).

Each R&D variable was lagged relative to the dependent variable being tested by an average of

two years in order to approximate the effects of research outlays on future operating margin

percentages; their signs were highly significant in all six models tested. The signs of debt as a

proportion of total assets (leverage) ratios were positive (which was also not surprising since

interest expenses were deducted after calculating EBITDA); results suggested that carrying debt

was temporarily helpful to building a strategic posture that would sustain premium prices. The

capital intensity variable was negative when it was not significant; the sign of the assets-to-

employee ratio was significant and highly-significant in year4. The logarithm of assets variable

was positive and highly-significant in post-acquisition year5 and year7―suggesting that the cost

leadership strategy (which depended on scale economies and higher market share as a source

of advantage) grew more important as time passed and other sources of advantage proved to

be fleeting.

The sign of the wireline services variable was negative and weakly significant (if at all).

The sign of the wireless services variable was not significant in any specifications shown; nor


was the internet services variable. In the many specifications tested, a pattern emerged

whereby the sign of the wired (landline) services variable was initially negative but became pos-

itive and significant by the seventh post-acquisition year (reflecting the evolution of wireline

services into cash-cow status as the business faced declining demand and marginal firms yield-

ed their laggard customer lists to competitors with greater staying power). The coefficients of

the wireless services and internet access dummy variable followed the opposite pattern where-

by they started positive and became negative over time, suggesting that competitors in those

communications services suffered declining operating margin percentages over time.

Results from Exhibit 2 suggested a competitive scenario in which patents made positive

contributions to operating margin percentages during the early years when acquisitions were

being integrated, but their incremental impact waned unless firms’ technological diversification

was successful in continuing to expand the breadth of knowledge that their inventors synthe-

sized in patents over time. Hypothesis 1a is supported by results, but Hypothesis 1b cannot be

accepted.

--------------------- Exhibit 3 here

---------------------- Effect of patent scores

Exhibit 3 illustrates results on operating margin percentages of specifications in which patent

score variables were substituted for the simple “having patents” variable tested in Exhibit 2.

Results shown in Exhibit 3 reflect the operating margin percentages of those firms for which

post-acquisition patent scores could be calculated (as contrasted with Exhibit 2 where all ac-

quiring firms were included for which financial information was available). There is some sup-

port for Hypotheses 2a and 2b because, in Exhibit 3 (which considers the effect of patent scores


on their return on sales ratios), the signs of all patent score variables were positive and statisti-

cally-significant―which suggests that creating patents which integrate larger proportions of

non-core knowledge will continue to influence firms’ operating margin percentages positively

for a greater duration.

Firms’ average patent score values trended towards mean values over time―perhaps

because individual firms no longer synthesized knowledge in their patents that was far from

their comfort zones (as was reflected by the technology class codes in which their subsequent

patents were granted). Or perhaps their patent scores trended towards mean values over time

because industrywide technology convergence had evolved in such a manner that when partic-

ular combinations of technology dyads appeared together as knowledge antecedents in any

particular patent’s grant, those technology class codes were no longer extraordinary in their

nature vis-à-vis what competitor firms were synthesizing in their respective inventions. The pa-

tent scoring methodology weighted the impact of out-of-the-box technology antecedents more

heavily than backward citations of technology class codes that were the same as those technol-

ogy class codes in which the patent’s claims were granted; in Exhibit 3, having many out-of-the-

box patents continued to improve firms’ return on sales ratios―even in year7.

In Exhibit 3, the signs of all ratios of research and development-to-sales variables were

negative and statistically-significant (which was not surprising since R&D expenses were de-

ducted from gross margin when computing return on sales). The post-acquisition significance of

the R&D-to-sales coefficients decreased over time. When the research productivity variable

―measured as the ratio of patents-to-R&D expenses―was tested, it was positive and weakly


significant (which suggested that high R&D productivity improved firms’ returns on sales and

sustained the duration of their patent-based competitive advantage).

Signs were positive and statistically-significant for the coefficient of the assets-per-

employees variable (representing capital intensity) as well as for the logarithm-of-assets varia-

ble (suggesting the presence of scale economies). The diversification variable was weakly signif-

icant and not included in specifications as the number of usable observations decreased. (The

population of usable post-acquisition observations decreased over time because 48.5 percent

of the acquiring firms were themselves acquired by 2012 and another 9.9 percent of the acquir-

ing firms became insolvent. On average, the subsequent transactions by which acquiring firms

were themselves acquired occurred five years after the acquisition that closed in year0. )

Tests of the line of business dummy variables in Exhibit 3 again indicated that wired

communications services (landlines) were negatively-signed and significant in the early post-

acquisition years, but became positive and significant by year7. Although it was not statistically-

significant in Exhibit 3, the sign of the wireless services variable was negative over time. The

internet services variable was negative and significant by year7 (but not by year4). Consistent

with findings from Exhibit 2, results indicated that firms’ operating margin percentages were

eroded by competing in hotly-contested lines of business during those years when their respec-

tive, apparent attractiveness attracted entry; by contrast the relatively fewer competitors that

provided services which faced declining demand enjoyed a positive impact on their operating

margins. Results suggested that endgame businesses offered opportunities for higher operat-

ing margin percentages than did those businesses for which demand was still growing and the

nature of competitive rules for some lines of business were still emerging. Results suggest that


firms’ higher return on sales ratios may have been due, in part, to their continued participation

in lines of business for which demand was declining (Harrigan, 1980).

--------------------- Exhibit 4 here

---------------------- Effect of changes in patent scores and R&D expenditures

Results of our tests of the effects of change variables were limited by the small sample sizes

that resulted when comparing year-by-year patent scores; many firms in our sample were not

awarded patents in any of the years that we tracked. Where data were available, we found that

positive changes in post-acquisition patent scores were significantly associated with positive

changes in firms’ return on sales ratios for the first four years after a transaction; the sign of the

patent-score change variable became negative and significant in year5―which reflected the be-

ginning of the flattened pattern of incremental changes in operating margin percentages that

we observed in our sample which is shown in Figures 1 and 2. Some firms continued to include

radical technology class codes among the antecedents that were cited in their patents, but their

innovation was no longer rewarded by incremental improvements in return on sales ratios after

year6 for reasons that we have already speculated about (concerning changes in relative novel-

ty as industry structure evolved) .

None of the post-acquisition changes in R&D productivity variables that we specified

were significant predictors of changes in operating margin percentages in any of the years test-

ed. The logarithm of assets variable (denoting scale-economy advantages) was weakly-

significant only in the third model specified. Results suggest that patent-based sources of com-

petitive advantage were of limited duration in the communications services industry during the

years spanning 1998 through 2012. Year-by-year analysis suggests that surviving communica-


tions firms enjoyed limited competitive advantage from having patents―unless the content of

their patent scores indicated that firms were stretching the breadth of technological class codes

that were synthesized in their patent applications.

Discussion of Results and Implications

Results are unsettling since patents have long been viewed as providing a quasi-monopolistic

advantage over specific inventions for a specified period; firms spend on research and devel-

opment aggressively with the expectation that such outlays will be recovered through the abil-

ity to charge temporary monopoly rents for exploitation of their patented inventions. Results

suggest that competitive stakes increased dramatically for firms who were patenting within the

communications services industry where monopoly rents from patents could be collected for

no more than five years. Results support the findings of Bessen and Meurer (2008) and others

who argue for the abolishment of the patent system, in part because the system has unintend-

ed economic consequences.

Our tests using return on sales ratios were run on a sample of acquiring firms having

some degree of diversification into more than one line of business.4 Although the firms in our

sample were diversified to varying degrees, we sorted the observations by line of business (and

by year) to understand how operating margin percentages changed over time and noted that

firms having media properties within their corporate families enjoyed positive average return

on sales margins; sorting the sample on all other lines of business yielded negative average op-

erating margin percentages for the period of 1998 through 2000. By 2001, firms having broad-

4 Approximately 55 percent of the acquiring firms were single-business entities; 79 percent of them were en-gaged in at two NAICS-defined lines of business and 90 percent of them were engaged in at least three lines of business when the acquisitions occurred. Roughly 45 percent of the target firms were single-business enti-ties; 68 percent of targets were engaged in only two (or fewer) NAICS-defined lines of business and only 79 percent of them were engaged in three (or fewer) lines of business when the acquisitions occurred.


cast assets in their corporate families enjoyed positive average return on sales margins (but av-

erage operating margin percentages were sometimes negative in subsequent years for this

sorting). Average operating margin percentages became positive for wired (landlines) commu-

nications services in 2003―as well as for resellers of capacity from inter-exchange communica-

tions carriers. Average return on sales margins became positive in 2004 for firms having satel-

lite service providers in their corporate families. By 2006 firms offering wireless communica-

tions services enjoyed positive average return on sales margins (but their average operating

margin percentages were negative during 2008 through 2010 for this sorting). The average op-

eration margin percentages of firms engaged in cable network communications services

(among other lines of business) became positive in 2007. On average, the return on sales mar-

gins of firms that offered internet-related communications services (among other lines of busi-

ness) did not become positive until 2010. (When the sample was sorted on NAICS 517919, indi-

cating Internet services, firms’ average operating margin percentages remained negative until

2011.)

Limitations

Conclusions from our tests were limited because a more-thorough test of the sustainability of

patent-based advantages within the communications services industry should have compared

the profitability of non-acquiring firms with that of the firms in our sample. Unfortunately there

were few non-acquiring firms in the communications services industry who also held patents.

Acquisitions appeared to be the method by which firms grew within the highly-dynamic com-

munications services industry (while they also persisted in developing patentable innovations),

so our sample may have approximated the available universe of firms during 1998 through


2005. Tests were hindered for examining the effects of patents on return on sales by the high

proportion of acquiring firms who were themselves acquired after consummating the initial ac-

quisitions that put them into our window of observation.

Because there was less attrition among electronics firms who made acquisitions during

our window of 1998 through 2005, we also tested the duration of patent-based competitive

advantage using an electronics sample to compare their respective patterns with that of the

communications services firms; operating margin percentages were lower for the electronics

industry—suggesting an even more turbulent competitive setting. In the electronics sample,

the coefficient of the “having patents” variable was positive and significant for post-acquisition

years 1 and 2; then the signs of each post-acquisition year’s patent variable became negative

(but not significant until year6). The post-acquisition sign of having patents again became posi-

tive and significant in year6 in electronics and remained so until post-acquisition year10 (alt-

hough the coefficients were not always significant). Results suggest that patent-based ad-

vantages therein may also have been eroded during years of particularly intense competition in

the electronics industry―just as they were within the communications services industry.

So many studies have indicated that patents were valuable by using analysis of forward

patent citations that we also tested forward patent scores using the same construction meth-

odology (yielding scores with higher values for patents having citations from broadly-disparate

user groups). Tests of ROS4 and ROS7 (using 4-year averaged forward-patent scores that were

lagged by three years for tests of ROS7) and for ROS7 and ROS8 (using 7-year averaged forward-

patent scores) returned negative, significant results. Further investigation of the effects of year-

by-year forward-citation patent scores on firms’ operation profit margin percentages may be


warranted―as well as theoretical explanations for why these patent-score measures should be

negatively correlated with return on sales. Our preliminary conclusion of such results is that av-

erage operating margins are damaged by having the firms’ patents built upon by firms in di-

verse technological areas that created substitute products which competed with the firms’ in-

ventions (but results may be due to our lack of information about actual patent royalties that

were collected from users―if any).

Summary

Our results suggest that competitive advantages from patents are limited in duration. Results

concerning the predictive power of post-acquisition patent scores offer some respite for firms

that continue to patent their inventions―provided that firms’ research organizations continue

to integrate technological knowledge that is far from their traditional technological areas within

their respective inventions. Exploratory learning continues to be a mandatory organizational

activity for firms that intend to survive―especially within industries characterized by rapid

technological change.

Success at serving customers attracts entry―whether by new firms who were previously

lurking on an industry’s fringe or by nearby competitors (who make investments to reposition

themselves in order to serve the newly-attractive customers which they wish to capture).

Firms’ incremental investments go to those competitive arenas where there appear to be

promising returns and (unless demand is growing rapidly) those investments in assets and ca-

pabilities are followed by the inevitable excess capacity and price cutting behavior that is need-

ed for new entrants to reach breakeven volumes of sales. Even in rapidly-growing environments

where incumbent firms acquire to gain technology, competitive advantage from patent assets is


transient and the need to renew the firm’s resources and organizational capabilities never

ends.


References Aghion P. Bloom N. Blundell R. Griffith R. Howitt P. 2005. Competition and innovation: An in-

verted-U relationship. Quarterly Journal of Economics 120(2): 701-728. Ahuja G. Katila R. 2001. Technological acquisitions and the innovation performance of acquiring

firms: a longitudinal study. Strategic Management Journal 25(8): 197-220. Alcacer J, Gittelman M. 2006. How do I know what you know? Patent examiners and the gener-

ation of patent citations. Review of Economics and Statistics 88(4): 774-779. Arikan AM. McGahan AM. 2010. The development of capabilities in new firms. Strategic Man-

agement Journal 31: 1-18. Artz KW. Norman PM. Hatfield DE. et al. 2010. A longitudinal Study of the impact of R&D, pa-

tents, and product innovation on firm performance. Journal of Product Innovation Man-agement 27(5): 725-740.

Audia P. Locke EA. Smith KG. 2000. The paradox of success: an archival and laboratory study of

strategic persistence following a radical environmental change. Academy of Manage-ment Journal 43(5): 837-854.

Bain JS. 1956. Barriers to New Competition. Harvard University Press, Cambridge. Barney JB. 1986. Organizational culture: can it be a source of sustained competitive advantage?

Academy of Management Review 11(3): 656-665. Barney JB. 1991. Firm resources and sustained competitive advantage. Journal of Management

17(1): 99-120. Belenzon, S. 2011. Cumulative innovation and market value: Evidence from patent citations.

Economic Journal 122:265-285. Bessen J. 2008. The value of U.S. patents by owner and patent characteristics. Research Policy

37: 932–945. Bessen J. Meurer MJ. 2008. Patent Failure: How Judges, Bureaucrats and Lawyers Put Innova-

tors at Risk Princeton University Press, Princeton, NJ. Bettis RA. Hitt MA. 1995. Guest editors’ introduction to the special issue: technological trans-

formation and the new competitive landscape. Strategic Management Journal 16(S1): 7-19.


Bosworth D. Rogers M. 2001. Market value, R&D and intellectual property: an empirical analysis of large Australian firms. Economic Record 77: 323–337.

Breitzman, A., & Thomas, P. (2002). Using patent citation analysis to target/value M&A

candidates. Research Technology Management 45: 28-36. Bureau of Census. 2014. Statistical Abstract of the United States, Department of Commerce. Chen MJ. Lin HC. Michel JG. 2010. Navigating in a hypercompetitive environment: the roles of

action aggressiveness and TMT integration. Strategic Management Journal 31(13): 1410-1430.

Christensen C. 1997. The Innovator's Dilemma: When New Technologies Cause Great Firms Fail.

Boston: Harvard Business Press. Cloodt M. Hagedoorn J. Van Kranenburg H. 2006. Mergers and Acquisitions: their effect on the

innovative performance of companies in high-tech industries. Research Policy 35: 642-668.

Cockburn I. Griliches Z. 1988. Industry effects and appropriability measures in the stock market

valuation of R&D and patents. American Economic Review 88: 418–423. Cohen L. Diether K. Malloy C. 2013. Misvaluing innovation. Review of Financial Studies 26(3):

635-666. Cohen WM. Levin RC. 1989. Empirical studies of innovation and market structure. In Schma-

lensee R. Willig RD. eds. Handbook of Industrial Organization Vol. 2. Elsevier Science. Amsterdam, North-Holland.

Cohen WM. Levinthal DA. 1990. Absorptive capacity: a new perspective on learning and inven-

tion. Administrative Science Quarterly 35: 128-152. Collis DJ. 1994. How valuable are organizational capabilities? Strategic Management Journal 15:

143-152. D’Aveni RA. 1994. Hypercompetition: Managing the Dynamics of Strategic Maneuvering Free

Press. NY D’Aveni RA. Dagnino GB. Smith KG. 2010. Guest editors’ introduction to the special issue: the

age of temporary advantage. Strategic Management Journal 31: 1371-1385. Dahlin KB. Behrens DM. 2005. When is an invention really radical? Defining and measuring

technological radicalness. Research Policy 34: 717-737.


Dierickx I. Kool K. 1989. Asset stock accumulation and the sustainability of competitive ad-vantage. Management Science 35: 1504-1511.

Drucker PF. 1999. Knowledge-worker productivity: The biggest challenge. California Manage-

ment Review 41(2): 79-94. Escribano A. Fosfuri A. Tribo JA. 2009. Managing external knowledge flows: the moderating role

of absorptive capacity. Research Policy 38(1): 96-105. Gambardella A. 1992. Competitive advantages from in-house scientific-research - the united-

states pharmaceutical-industry in the 1980s. Research Policy 21(5): 391-407. Gambardella A. Torrisi S. 1998. Does technological convergence imply convergence in markets?

evidence from the electronics industry. Research Policy. 27: 445-463. Gambardella A. Harhoff D. Verspagen B. 2008. The value of European patents. European Man-

agement Review 5: 69–84. Garcia, R, Calantone, R. 2002. A critical look at technological innovation typology and innova-

tiveness terminology: a literature review. Journal of Product Innovation Management 19(2): 110-132.

Gittelman M. 2008. A note on the value of patents as indicators of innovation: implications for

management research. Academy of Management Perspectives 22: 21-27. Green, SG, Gavin, MB, Aiman-Smith, L. 1995. Assessing a multidimensional measure of radical

technological innovation. IEEE Transactions on Engineering Management 42(3): 203-214.

Griliches Z. 1981. Market value, R&D, and patents. Economic Letters 7: 183–187. Groysberg B. Lee LE. Nanda A. 2008. Can they take it with them? The portability of star

knowledge workers' performance. Management Science 54(7): 1213-1230. Hall BH. Jaffe AB. Trajtenberg M. 2005. Market value and patent citations. Rand Journal of Eco-

nomics 36(1): 16-38. Hall BH. Jaffe AB. and Trajtenberg M. 2001. The NBER patent citations data file: Lessons, in-

sights and methodological tools. NBER working paper no. 8498. Harhoff D. Narin F. Scherer FM. et al. 1999. Citation frequency and the value of patented inven-

tions. Review of Economics and Statistics 81(3): 511-515.


Harrigan KR. 1980. Strategies for Declining Businesses, D.C. Heath & Company, Lexington Books, Lexington, MA.

Harrigan KR. 1985. Strategies for Joint Ventures, D.C. Heath & Company, Lexington Books, Lex-

ington, MA. Harrigan KR. Dalmia G. 1991. Knowledge workers: the last bastion of competitive advantage,”

Planning Review 19(6): 4-7. Hegde D. Sampat B. 2009. Examiner citations, applicant citations, and the private value of pa-

tents. Economics Letters 105(3): 287-289. Helfat CE. Peteraf MA. 2003. The dynamic resource-based view: capabilities life cycles. Strategic

Management Journal 24(10): 997-1010. Henderson R. 1993. Underinvestment and incompetence as responses to radical innovation:

evidence from the photolithographic alignment equipment industry. Rand Journal of Economics 24:248-270.

Jaffe A. 1986. Technological opportunity and spillovers of R&D: evidence from firms’ patents,

profits, and market value. American Economic Review 76: 984–1001. Jaffe AB. Fogarty MS. Banks BA. 1998. Evidence from patents and patent citations on the im-

pact of NASA and other federal labs on commercial innovation. Journal of Industrial Economics 46(2): 183-205.

Jaffe AB. Trajtenberg M. Fogarty MS. 2000. Knowledge spillovers and patent citations: Evidence

from a survey of inventors. American Economic Review 90(2): 215-218. Johnson DKN. Popp D. 2003. Forced out of the closet: the impact of the American Inventors

Protection Act on the timing of patent disclosure. RAND Journal of Economics. 34(1): 96-112.

Kamien MI. Schwartz NL. 1974. Patent life and R&D rivalry. American Economic Review 64(1):

183-187. Kelley DJ. Ali A. Zahra SA. 2013. Where do breakthroughs come from? characteristics of high-

potential inventions. Journal of Product Innovation Management 30(6): 1212-1226. Kim C. Song J. Nerkar A. 2012. Learning and innovation: Exploitation and exploration trade-offs.

Journal of Business Research 65: 1189-1194. Lane PJ. Balaji RK. Pathak S. 2006. The reification of absorptive capacity: a critical review and

rejuvenation of the construct. Academy of Management Review 31: 883-863.


Lane PJ. Lubatkin M. 1998. Relative absorptive capacity and interorganizational learning. Stra-

tegic Management Journal 19(5): 461-477. Lanjouw JO. 1998. Patent protection in the shadow of infringement: simulation estimations of

patent value. Review of Economic Studies 65: 671–710. Lanjouw JO. Pakes A. Putnam J. 1998. How to count patents and value intellectual property: the

uses of patent renewal and application data. Journal of Industrial Economics 46: 405–432.

Lee YG. Lee JD. Song YI. Lee SJ. 2007. An in-depth empirical analysis of patent citation counts

using zero-inflated count data model: the case of KIST. Scientometrics 70(1): 27-39. Lin C. Wu YJ. Chang C. Wang W. Lee CY. 2012. The alliance innovation performance of R&D alli-

ances―the absorptive capacity perspective. Technovation 32(5): 282-292. Makri M. Hitt MA. Lane PJ. 2010. Complementary technologies, knowledge relatedness, and

invention outcomes in high technology mergers and acquisitions. Strategic Management Journal 31(6): 602-628.

Malerba F. 2006. Innovation and the evolution of industries. Journal of Evolutionary Economics.

16(2): 3-21. March JG. 1991. Exploration and exploitation in organizational learning. Organization Science

2:71-87. Mazzucato M. Tancioni M. 2012. R&D, patents and stock return volatility. Journal of Evolution-

ary Economics 22(4): 811-832. McGahan AM. Porter ME. 1999. The persistence of shocks to profitability. The Review of Eco-

nomics and Statistics 81(1): 143-153 McGahan AM. Silverman BS. 2006. Profiting from technological innovation by others: the effect

of competitor patenting on firm value. Research Policy 35: 1222–1242. McGrath RG. 2001. Exploratory learning, innovative capacity, and managerial oversight. Acad-

emy of Management Journal 44(1): 118–131. McGrath RG. 2013. The End of Competitive Advantage: How to Keep Your Strategy Moving as

Fast as Your Business Harvard Business Review Press. Cambridge, MA. Mowery DC. Rosenberg N. 1998. Paths of Innovation: Technological Change in 20th-Century

America. Cambridge University Press: Cambridge.


Nelson RR. Winter SG. 1982. An Evolutionary Theory of Economic Change. Belknap Harvard:

Cambridge. Nooteboom B. Van Haverbeke W. Duysters G. Gilsing V. van den Oord A. 2007. Optimal

cognitive distance and absorptive capacity. Research Policy 36: 1016-1034. Novak S. Stern S. 2008. How does outsourcing affect performance dynamics? evidence from the

automobile industry, Management Science 54(12): 1963-1979. Novak S. Stern S. 2009. Complementarity among vertical integration decisions: evidence from

automobile product development, Management Science 55(2): 311-332. Patel D. Ward MR. 2011. Using patent citation patterns to infer innovation market competition.

Research Policy 40(6): 886-894. Peteraf MA. 1993. The cornerstones of competitive advantage: a resource-based view. Strategic

Management Journal 14(3): 179–191 Porter ME. 1980. Competitive Strategy: Techniques for Analyzing Industries and Competitors

Free Press, New York. Porter ME. 1991. Towards a dynamic theory of strategy. Strategic Management Journal 12: 95-

117. Porter ME. 1996. What is strategy? Harvard Business Review 74(6): 61-78. Powell TC. DentMicallef A. 1997. Information technology as competitive advantage: The role of

human, business, and technology resources. Strategic Management Journal 18(5): 375-405.

Reitzig M. 2004. Improving patent valuations for management purposes—validating new indi-

cators by analyzing application rationales. Research Policy 33: 939-957. Rosenkopf L. Nerkar A. 2001. Beyond local search: Boundary-spanning, exploration, and impact

in the optical disk industry. Strategic Management Journal 22: 287-306. Ruefli TW. Wiggins RR. 2003. Industry, corporate, and segment effects and business perfor-

mance: a non-parametric approach. Strategic Management Journal 24(9): 861-879. Sandner PG. Block J. 2011. The market value of R&D, patents and trademarks. Research Policy

40: 969-985.


Schankerman M. 1998. How valuable is patent protection? Estimates by technology field. RAND Journal of Economics 29(1): 77-107.

Scherer FM. 1967. Market structure and the employment of scientists and engineers. American

Economic Review 57(3): 524-531. Scherer FM. Harhoff D. 2000. Technology policy for a world of skew-distributed outcomes. Re-

seach Policy 29(4-5): 559-566. Schoenmakers W. Duysters G. 2010. The technological origins of radical inventions. Research

Policy 39: 1051-1059. Schreyögg G, Kliesch-Eberl M. 2007. How dynamic can organizational capabilities be? Toward a

dual process model of capability dynamization. Strategic Management Journal 28(9): 913–933.

Schumpeter JA 1912. The Theory of Economic Development Cambridge University Press, Cam-

bridge. Schumpeter JA. 1942. Capitalism, Socialism and Democracy Harper and Brothers, New York Silverberg G. Verspagen B. 2007. The size distribution of innovation revisited: An application of

extreme value statistics to citation and valuation measures of patent significance. Jour-nal of Econometrics 139: 318-339.

Sorensen JB. Stuart TE. 2000. Aging, obsolescence and organizational innovation. Administrative

Science Quarterly 45: 81-112.

Teece DJ. Pisano G. Shuen A. 1997. Dynamic capabilities and strategic management. Strategic Management Journal 18(7): 509-533.

Thomas LG. 1996. The two faces of competition: dynamic resourcefulness and the hypercom-petitive shift. Organization Science 7: 221-242.

Thomson Reuters. 2013. Derwent World Patents Index Classification Guide. Philadelphia: Web of Science.

Thomson Reuters. 2013. Thomson One Mergers & Acquisitions. SDC Platinum Database.

Tirole J. 1988. The Theory of Industrial Organization The MIT Press, Cambridge, MA 3rd Edition. Trajtenberg M. 1990. A penny for your quotes: patent citations and the value of innovations.

RAND Journal of Economics 21: 172-187.


Trajtenberg M. Henderson R. Jaffe A. 1997. University versus corporate patents: A window on

the basicness of invention. Economics of Innovation and New Technology, 5: 19–50. Tsai KH. 2009. Collaborative networks and product innovation performance: toward a

contingency perspective. Research Policy 38(5): 765-778.

Tushman ML. Anderson P. 1986. Technological discontinuities and organizational environments. Administrative Science Quarterly 31: 439-465.

Villalonga B. 2004. Intangible resources, Tobin’s q, and sustainability of performance differ-ences. Journal of Economic Behavior & Organization 54: 205–230.

Volberda HW. Foss NJ. Lyles MA. 2010. Absorbing the concept of absorptive capacity: how to realize its potential in the organization field. Organization Science 21: 931-951.

Wernerfelt B. 1995. A resource-based view of the firm. Strategic Management Journal 5(2): 171–180

Zamojcin, T. 2013. Personal communication and interview notes. Thomson Reuters: NY. 6 Au-gust 2013.


Figure 1

-20%

-10%

0%

10%

20%

30%

40%

Post-Acquisition Return on Sales for All Transactions

Always Patents Before Only After Only Never Patents


Figure 2 Comparison of Return on Sales by Year of Acquisition

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7 ROS8 ROS9 ROS10

Post-Acquisition Return on Sales for 1998 Transactions

Both Before/ After Before Only After Only No Patents

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

60%


Post-acquisition Return on Sales for 1999 Transactions



Figure 2 (continued)

-60%

-40%

-20%

0%

20%

40%

60%




-60%

-40%

-20%

0%

20%

40%

60%






-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%




-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7 ROS8 ROS9





0%

10%

20%

30%

40%

50%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7 ROS8



0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7




Figure 3 Comparison of Post-Acquisition Return on Sales by Backward-Citation Patent Scores

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%


Average Post-Acquisition Return on Sales

High Scores Low Scores No Patents


Figure 4 Year-by-Year Comparison of Return on Sales by Backward-Citation Patent Scores

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%




-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%






-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%




-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%






-20%

-10%

0%

10%

20%

30%

40%




-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7 ROS8 ROS9





-20%

-10%

0%

10%

20%

30%

40%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7 ROS8



0%

5%

10%

15%

20%

25%

30%

35%

40%

ROS0 ROS1 ROS2 ROS3 ROS4 ROS5 ROS6 ROS7




Exhibit 1a

Means for Having Patents

N Mean Std Dev Minimum Maximum

1 LogAssets0 441 3.26115 1.17469 -0.91364 5.9414

2 LogAssets1 543 3.22743 1.17613 -0.70774 5.98373

3 LogAssets4 414 3.22146 1.1977 -0.91364 5.87535

4 LogAssets7 317 3.4574 1.15493 -0.30103 5.90055

5 Productivity0 393 0.31867 0.39453 0.001 4.89267

6 Productivity1 469 0.38561 1.06022 0.00119 19.991

7 Productivity7 299 1.06584 4.90317 0.00741 71.9765

8 Assets/ Employees0 351 14.5074 102.334 0.02146 1732

9 Assets/ Employees1 460 19.3452 136.348 0 2289

10 Assets/ Employees7 300 3.16357 11.2369 0.05033 108.7581

11 Intangibles/ All Assets0 287 0.22295 0.21047 0 0.89174

12 Intangibles/ All Assets1 391 0.2086 0.21297 2.84E-06 0.95649

13 Intangibles/ All Assets7 293 0.31621 0.21667 0.000262 0.83651

14 Long-Term Debt/ Assets4 359 0.35301 0.24614 0.00016 0.95498

15 Has Patents 606 0.59406 0.49148 0 1

16 Landline (Wired) Services 606 0.72277 0.448 0 1

17 Wireless Services 606 0.49505 0.50039 0 1

18 Internet Services 606 0.19142 0.39374 0 1


Exhibit 1b

Correlations for Having Patents

1 LogAssets0 1 2 3 4 5 6 7 8 9 10

2 LogAssets1 0.86732

<.0001

414

3 LogAssets4 0.73134 0.80404

<.0001 <.0001

300 386

4 LogAssets7 0.73579 0.80052 0.93833

<.0001 <.0001 <.0001

225 288 307

5 Productivity0 0.09357 0.01006 0.21193 0.13623

0.0804 0.8478 0.0004 0.0492

350 366 275 209

6 Productivity1 -0.1282 -0.0885 0.03703 0.24831 0.32478

0.0155 0.0612 0.4956 <.0001 <.0001

356 448 341 255 348

7 Productivity7 -0.0091 -0.0345 -0.0329 -0.0867 0.05344 0.01799

0.8953 0.5723 0.5768 0.1349 0.4535 0.778

213 271 291 299 199 248

8 Assets/ Employees0 0.17912 0.15129 -0.089 -0.1344 0.08889 0.02217 -0.0217

0.0007 0.0057 0.1648 0.0674 0.0969 0.6974 0.774

351 332 245 186 350 310 177

9 Assets/ Employees1 0.13273 0.11316 -0.0467 -0.0999 0.22399 0.01363 -0.0128 0.49829

0.0124 0.0157 0.3943 0.1158 <.0001 0.7723 0.8428 <.0001

354 455 335 249 340 453 241 307


10 Assets/ Employees7 -0.0419 -0.0206 -0.0107 0.01631 0.04044 0.19959 0.54159 -0.0261 -0.0006

0.5425 0.7353 0.8561 0.7784 0.5706 0.0016 <.0001 0.7303 0.9929

214 272 291 300 199 248 299 177 241

11 Intangibles/ Assets0 -0.1132 0.01737 0.06637 0.01634 -0.0064 -0.0475 -0.053 -0.1224 -0.1153 -0.0476

0.0553 0.7767 0.3432 0.8335 0.9178 0.464 0.507 0.0469 0.0759 0.551

287 269 206 168 263 240 159 264 238 159

12 Intangibles/ Assets1 -0.0174 -0.0965 0.13514 0.08644 0.07732 0.06106 -0.093 -0.1167 -0.139 -0.0975

0.7642 0.0566 0.0194 0.1934 0.207 0.256 0.1704 0.067 0.0092 0.1505

300 391 299 228 268 348 219 247 350 219

13 Intangibles/ Assets7 0.16798 0.1457 0.18817 0.21034 -0.009 -0.0602 -0.0265 -0.1484 -0.0987 -0.0672

0.0153 0.0176 0.0014 0.0003 0.9014 0.3549 0.6566 0.0513 0.1339 0.26

208 265 285 293 192 238 283 173 232 283

14 LT Debt/ Assets4 0.07418 0.10797 -0.0088 -0.0106 -0.0063 -0.0482 0.12918 0.03027 0.05021 0.24113

0.2288 0.049 0.8682 0.8621 0.9225 0.4076 0.0381 0.6567 0.3942 <.0001

265 333 359 273 241 297 258 218 290 258

15 Has Patents 0.34531 0.33698 0.39524 0.34789 0.01431 -0.0685 -0.1244 -0.0337 -0.0845 -0.0961

<.0001 <.0001 <.0001 <.0001 0.7773 0.1386 0.0315 0.5295 0.0701 0.0966

441 543 414 317 393 469 299 351 460 300

16 Landline Services 0.0126 0.06 0.09351 0.0995 -0.0471 0.03451 0.01011 -0.0768 -0.1321 -0.071

0.7919 0.1627 0.0573 0.0769 0.3514 0.4559 0.8619 0.1512 0.0045 0.22

441 543 414 317 393 469 299 351 460 300

17 Wireless Services 0.10128 0.06866 0.08966 0.05062 0.0645 0.08022 -0.0453 0.00292 0.00357 0.04061

0.0335 0.11 0.0684 0.369 0.202 0.0827 0.4352 0.9565 0.9391 0.4835

441 543 414 317 393 469 299 351 460 300

18 Internet Services 0.27734 0.26475 0.26194 0.23929 -0.0063 -0.0147 0.01586 0.00041 -0.0109 0.11641

<.0001 <.0001 <.0001 <.0001 0.9008 0.7509 0.7848 0.9939 0.816 0.0439

441 543 414 317 393 469 299 351 460 300


11 12 13 14 15 16 17

10 Assets/ Employees7

11 Intangibles/ All Assets0

12 Intangibles/ All Assets1 0.69336

<.0001

238

13 Intangibles/ All Assets7 0.23217 0.46054

0.0032 <.0001

159 217

14 Long-Term Debt/ Assets4 -0.0333 -0.079 -0.0572

0.6499 0.199 0.3605

188 266 258

15 Has Patents 0.03963 0.04928 0.13374 -0.2338

0.5037 0.3311 0.022 <.0001

287 391 293 359

16 Landline (Wired) Services -0.0595 -0.0156 0.01234 0.07484 -0.1141

0.3149 0.759 0.8334 0.1571 0.0049

287 391 293 359 606

17 Wireless Services 0.10435 0.0816 -0.0166 -0.0468 0.03214 -0.2642

0.0776 0.1072 0.7772 0.3766 0.4297 <.0001

287 391 293 359 606 606

18 Internet Services 0.02119 0.08011 0.14041 0.06953 0.16305 0.16078 0.06354

0.7208 0.1137 0.0162 0.1887 <.0001 <.0001 0.1182

287 391 293 359 606 606 606


Exhibit 1c

Means for Patent Scores

N Mean Std Dev Minimum Maximum

1 Return on Sales3 438 -0.11279 3.53648 -69.4362 0.72962

2 Return on Sales5 386 0.11009 1.02957 -13.0874 0.69196

3 Return on Sales7 318 -0.01984 3.07646 -51.8492 0.66735

4 Backward Citation Score be-fore Acquisition (7-year aver-age)

286 33.5651 16.6928 0.05 126.9924

5 Backward Citation Score of 4th Year after Acquisition

155 39.6325 36.0023 0.05 321.3153

6 Backward Citation Score after Acquisition (7-year average)

303 38.5932 31.2296 0.05 269.6336

7 LogAssets3 443 3.36328 1.12241 -0.23062 6.0368

8 LogAssets5 390 3.29129 1.18478 -1.55284 5.82822

9 LogAssets7 317 3.4574 1.15493 -0.30103 5.90055

10 Productivity3 401 0.60186 2.26034 0.00362 29.7416

11 Productivity5 354 0.68751 2.33556 0.01356 29.34458



14 R&D Expense/ Sales7 98 0.13455 0.61921 0.00108 6.10684

15 Patents in Year5/ R&D Costs5 93 2.95391 17.1839 0 140

16 Landline (Wired) Services 606 0.72277 0.448 0 1

17 Wireless Services 606 0.49505 0.50039 0 1

18 Internet Services 606 0.19142 0.39374 0 1


Exhibit 1d

Correlations for Patent Scores

1 2 3 4 5 6 7 8 9

1 Return on Sales3

2 Return on Sales5 0.53619

<.0001

372

3 Return on Sales7 0.09306 0.26441

0.1042 <.0001

306 315

4 Backward Citation Score before Acquisition (7-year average)

0.15333 0.16301 0.16095

0.0223 0.0205 0.0314

222 202 179

5 Backward Citation Score of 4th Year after Acquisition

0.05538 0.08951 0.06353 0.1746

0.5173 0.3169 0.5116 0.0436

139 127 109 134

6 Backward Citation Score after Acquisition (7-year average)

-0.0117 0.04738 0.09574 0.31769 0.6513

0.8545 0.4746 0.1808 <.0001 <.0001

249 230 197 229 155


7 LogAssets3 0.1638 0.25117 0.14787 0.1108 -0.1113 -0.0448

0.0014 <.0001 0.0141 0.0966 0.2006 0.4845

380 331 275 226 134 246

8 LogAssets5 0.18422 0.27505 0.1827 0.1538 -0.1306 0.03499 0.83665

0.0004 <.0001 0.0012 0.0289 0.1465 0.6 <.0001

372 383 313 202 125 227 335

9 LogAssets7 0.17688 0.26787 0.21482 0.24705 -0.1585 0.01782 0.79324 0.95336

0.002 <.0001 0.0001 0.0009 0.1047 0.8058 <.0001 <.0001

302 311 314 178 106 193 273 313

10 Productivity3 0.0322 0.06396 0.03446 0.02883 0.07039 -0.0426 0.06213 0.02077 0.06575

0.5203 0.2388 0.5658 0.6801 0.4262 0.5239 0.247 0.7019 0.2746

401 341 280 207 130 226 349 342 278

11 Productivity5 0.03539 0.0722 0.03447 0.12776 0.04947 -0.0491 0.07092 0.02852 0.06258

0.5105 0.1753 0.5595 0.079 0.59 0.4772 0.2153 0.5928 0.2898

348 354 289 190 121 212 307 354 288

12 Assets/ Employees5 0.02694 0.04472 0.02972 0.02748 0.31964 0.14467 0.07562 0.03263 0.07473

0.6165 0.4015 0.6148 0.7066 0.0004 0.0353 0.1856 0.54 0.206

348 354 289 190 121 212 308 355 288

13 Assets/ Employees7 0.02899 0.03498 0.0602 0.09393 -0.0694 0.04287 -0.0227 0.00848 0.01631

0.6236 0.5482 0.2995 0.2231 0.4882 0.5634 0.7169 0.8843 0.7784

289 297 299 170 102 184 257 297 300

14 R&D Expense/ Sales7 -0.1186 -0.845 -0.9046 -0.2351 0.03235 -0.163 -0.195 -0.1705 -0.2006

0.2474 <.0001 <.0001 0.0335 0.8254 0.1459 0.0738 0.0932 0.0477

97 98 98 82 49 81 85 98 98


15 Patents in Year5/ R&D Costs5

0.01849 0.00823 -0.0188 -0.1482 -0.065 -0.0097 0.02036 -0.2187 -0.1956

0.8603 0.9376 0.8655 0.176 0.6371 0.9277 0.8605 0.0352 0.0746

93 93 84 85 55 90 77 93 84

16 Landline (Wired) Services 0.10699 0.10427 0.01318 0.18777 0.0551 -0.067 0.0859 0.06732 0.0995

0.0251 0.0406 0.8149 0.0014 0.4959 0.2448 0.0709 0.1846 0.0769

438 386 318 286 155 303 443 390 317

17 Wireless Services 0.06397 0.05034 0.06901 -0.1026 -0.1011 0.06144 0.03848 0.08385 0.05062

0.1814 0.3239 0.2197 0.0833 0.2105 0.2864 0.4191 0.0982 0.369

438 386 318 286 155 303 443 390 317

18 Internet Services -0.0738 0.03198 0.04795 0.16814 0.08041 0.13908 0.27494 0.2711 0.23929

0.1231 0.5311 0.3941 0.0044 0.3199 0.0154 <.0001 <.0001 <.0001

438 386 318 286 155 303 443 390 317


10 11 12 13 14 15 16 17

10 Productivity3

11 Productivity5 0.94111

<.0001

330

12 Assets/ Employees5 0.94561 0.94448

<.0001 <.0001

330 354

13 Assets/ Employees7 0.87831 0.89594 0.96236

<.0001 <.0001 <.0001

271 280 280

14 R&D Expense/ Sales7 -0.1915 -0.1935 0.04937 -0.038

0.063 0.0603 0.6347 0.7135

95 95 95 96

15 Patents in Year5/ R&D Costs5 0.00657 -0.1003 -0.1066 -0.0934 -0.1231

0.951 0.3442 0.3147 0.4039 0.2797

90 91 91 82 79

16 Landline (Wired) Services -0.0814 -0.0584 -0.1113 -0.071 0.02128 0.08928

0.1036 0.2729 0.0362 0.22 0.8353 0.3948

401 354 355 300 98 93

17 Wireless Services 0.04621 0.02323 0.03832 0.04061 0.05438 -0.1482 -0.2642

0.356 0.6631 0.4717 0.4835 0.5949 0.1562 <.0001

401 354 355 300 98 93 606

18 Internet Services -0.014 -0.0161 -0.0105 0.11641 -0.0496 0.13538 0.16078 0.06354

0.7795 0.7628 0.8433 0.0439 0.628 0.1957 <.0001 0.1182

401 354 355 300 98 93 606 606


Exhibit 2

Effect of Having Patents on EBITDA Divided by Sales (ROS)

1 2 3 4 5 6

ROS ROS ROS ROS ROS ROS

1 year after 2 years after 3 years after 4 years after 5 years after 7 years after

acquisition acquisition acquisition acquisition acquisition acquisition

Intercept -0.23989 -0.39686 0.00590 0.04195 0.07382 -0.05142

0.14066 0.13596 0.14697 0.05503 0.09286 0.08851

† ** NS NS NS NS

Having Patents 0.34759 0.52083 0.21385 0.10494 -0.14170 -0.00093

0.10065 0.11060 0.10578 0.04770 0.07139 0.06965

** *** * * * NS

R&D/ Sales -1.69775a -2.12316b -1.26252c -0.68853d -0.80081e -1.00328f

0.18353 0.42484 0.21761 0.13611 0.18544 0.16384

*** *** *** *** *** ***

Long-Term Debt/ Total Assets 0.27663 0.51471 0.24991 -- -- --

0.16278 0.22481 0.13409

† * †

Assets per Employee -0.00003 -0.00009 -0.00015 0.07534 -- --

0.00095 0.00077 0.00079 0.01026

NS NS NS ***





LogAssets -- -- -- -- 0.09662 0.07222

0.02330 0.01729

*** ***

Landline (Wired) Services -0.00160 0.10358 -0.17599 -0.01936 -0.13901 0.04913

0.08695 0.10218 0.09302 0.03687 0.05420 0.04599

NS NS † NS * NS

Wireless Services 0.05513 -- 0.10484 -- -- -0.04852

0.07366

0.07822

0.04054

NS

NS

NS

Internet Services 0.06859 -- 0.10781 -0.00848 0.03466 -0.05944

0.09859

0.08688 0.03978 0.06236 0.05069

NS

NS NS NS NS

Adjusted R2 0.4831 0.4564 0.3886 0.4673 0.4177 0.5326

Observations 108 68 85 106 108 96

*** < 0.001 ** 0.01 * 0.05 † 0.10


Exhibit 3

Effect of Patent Scores on EBITDA Divided by Sales (ROS)

1 2 3 4 5 6




Intercept -0.27700 0.06360 -0.04893 -0.29845 -0.32998 -0.18730

0.20642 0.13858 0.07296 0.06628 0.11559 0.09177

NS NS NS *** ** **

Backward Patent Scores 0.00990a 0.00117b 0.00218c 0.00152d 0.00271e 0.00134f

0.0039 0.00052 0.00078 0.00034 0.00113 0.00047

* * † *** * **

R&D Expense / Sales -1.27817 -0.70849 -0.37648 -- -0.64266 -0.72204

0.23563 0.16295 0.15613

0.28723 0.28218

*** *** *

* *

Patents/ R&D Expense -- -- -- 0.00131 -- --

0.00037

†

Assets per Employee -- -- 0.06958 -- 0.07749 --

0.01599

0.02788

***

**





LogAssets 0.01148 0.05560 0.05583 0.10619 0.08786 0.08524

0.04123 0.02827 0.01559 0.01604 0.02202 0.01914

NS † ** *** ** ***

Long-term debt/ Total Assets -- -- -- -0.10217 -- --

0.11579

NS

Diversification 0.55251 -- -- -- -- --

0.28301

†

Wired Services -- -0.16929 -0.10471 -- 0.10756 --

0.08228 0.04023

0.06126

* *

†

Wireless Services -- -- -0.04638 -- -0.06478 --

0.03485

0.05141

NS

NS

Internet Services -- -- -0.02132 -- -0.14816 --

0.04092

0.06021

NS

*


Adjusted R2 0.4386 0.4851 0.5282 0.5638 0.4806 0.5033

Observations 54 50 80 44 79 47

*** <0.0001 ** 0.01 * 0.05 † 0.10

a Year0 patent scores

b Year3 patent scores

c 4-year average patent scores

d Year4 patent scores

e 7-year average patent scores f Year4 patent scores


Exhibit 4

Effect of Changes in Patent Scores on Post-Acquisition Changes in Return on Sales

1 2 3 4 5

Year1 Year2 Year3 Year4 Year6

changes changes changes changes changes

in ROS in ROS in ROS in ROS in ROS

Intercept -0.19149 -0.61993

-0.93734 -1.09647 -0.37127

0.43343 0.62941 0.51811 0.84037 0.64965

NS NS † NS NS

Changes in 1.21333a 1.06224b 1.06288c 0.63334d -0.03819e

Patent Scores 0.11227 0.15819 0.13478 0.17854 0.00913

*** *** *** ** **

Changes in -0.00030 -- -- -- --

R&D Expense/ Assets 0.00892

NS

Changes in -- 0.18535

-0.21938 0.04639 0.27095

R&D Expense/ Patents

0.19484 0.18597 0.41801 0.34546

NS NS NS NS

LogAssets -0.01309 0.11701 0.23445 0.26811 0.12916

0.11017 0.15231 0.13039 0.20509 0.15897

NS NS † NS NS

Adjusted R2 0.7647 0.4856 0.5866 0.1674 0.3223

Observations 37 46 43 49 43

*** <0.0001 ** 0.01 * 0.05

a Difference of year1 score change from year0 score divided by year0 score

b Difference of year2 score change from year1 score divided by year1 score c Difference of year3 score change from year2 score divided by year2 score d Difference of year4 score change from year3 score divided by year3 score e Difference of year6 score change from year5 score divided by year5 score

SUSTAINABILITY OF PATENT-BASED … of Patent-based Competitive Advantage 3 Sustainability of...

Documents

Transcript of SUSTAINABILITY OF PATENT-BASED … of Patent-based Competitive Advantage 3 Sustainability of...