What managers should know about their competitors' patented technologies

What Managers Should Know about Their Competitors’ Patented Technologies William W. Keep Glenn S. Omura Roger J. Calantone This article examines the structure of technological research and the number of patents granted in a specific technological area. Results indicate that even in a single technological area, the level of research activity is strongly associated with the way research is structured among competing$rms. The results can help managers use accessible patent data to better understand the actions of technological competitors.

Address correspondence to Wdliam W. Keep, University of Kentucky, Department of Marketing, Room 345 Business & Economics Building, Lexington, KY 405060034. The authors express their appreciation to Forrest Carter and David Closs for their suggestions and critique early in the research process. They also received helpful comments from Ben Tepper, Pat Daugherty, and Brien Ellis.

Industrial

Q Elsevier

Marketing

Management

23, 257-264

(1994)

Science Inc., 1994 655 Avenue of the Americas, New York, NY 10010

INTRODUCTION Many industrial firms have highly interesting technologies “on the shelf.” These are not incorporated into products or manufacturing processes yet, but they are a “hope” for the future. Naturally, competitors have similar stores of technologies. When these technologies emerge, the innovating firm can “breakout” competitively. If firms nxarch their competitors’ technological activity, they can anticipate and even pre-empt innovations before they reach the market. Patenting information is highly accessible data that can provide managers with an important historical record of many technologies and suggest areas of future innovations [l]. Strategic analysis of patent activity can bring increased understanding of the research process into strategic planning. Patent analysis can be used to: (1) Compare the rela-

257 0019.8501/94/$7.00

Patent data can anticipate technology developments. tive technological strengths of competing firms; (2) assess acquisition and joint venture opportunities; (3) help classify patents based on value and potential; (4) analyze the pace of R&D in evolving technologies; and (5) help bridge the gap between technological development and marketable innovations [2]. Recent studies have used patent data to identify firms who were well-positioned to be market leaders in the battery industry; to highlight technological areas that provide the best licensing opportunities; and to show how technological activity anticipates commercial applications [3]. One study also demonstrated how ignoring the “research fit” of acquired firms can lower R&D output and reduce the combined firm’s overall patent activity [4]. These studies show how patent analysis is beginning to help managers interpret rapidly changing technologies and why it is important to learn more about the impact of competitive relationships on patent activity. The current study applies industrial organization (IO) theory to the study of the technological process that leads to patenting by examining the industry structure-industry performance relationship. The current research adopts this approach in a way that allows managers to see how the strncture of research in narrowly defined technology areas can affect the amount of patent activity in those areas. The current study also provides ways to measure the structure of industry research.

PATENT RESEARCH AND CORPORATE STRATEGY Recent patent-based research is technology specific and managerially relevant. For example, researchers have used patent data to measure the importance of a single patent in the subsequent development of a family of competing patents in both the pharmaceutical and electronics industries, and to track trends in microgenetic engineering [5, 6, 71. Studies of patenting patterns have shown that the number of patents granted to companies is positively related to corporate technological strength, as perceived by industry experts, and to company profits and sales [5]. Research has also demonstrated the centralization of patenting activity in multinational corporations, and the positive relationship between patent activity and the technological strength of countries [8, 93. In addition, the tendency to patent has nor decreased over time [lo]. These studies have a two-fold effect on the current research. First, they show how patent data can be used to track and even anticipate change in specific technologies. And second, they provide clues to new methods of measuring competitive relationships. Both of these are important considerations for managers responsible for strategic planning. The current article extends existing research by identify competitive factors that affect the pace of R&D in evolving technologies.

USING AN INDUSTRIAL ORGANIZATION MODEL WILLIAM W. KEEP is Assistant Professor of Marketing University of Kentucky. GLENN S. OMURA is Associate Professor of Marketing Michigan State University.

at

at

ROGER J. CALANTONE is Professor of Marketing at Michigan State University.

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Industrial organization (IO) economists conducted much of the early technological change research that included competitive relationships [cf. 11, 121. These studies looked at a variety of industry variables, such as the number of competing firms and the degree of economic concentration in the industry. Frequently, the competitive industry was defined as those firms operating within the same Standard Industrial Classification (SIC) area or manufacturing

Industry concentration has an impact on technology. the same product. Although significant results were found, the broad industry definition and the multitechnology nature of most products prevented the research from being technology specific. The present research redefines “industry” as a speczjk technology area. In United States Patent and Trademark Office (USPTO) terms, each specific technology area is apatent subclass. Those firms researching in a patent subclass are considered to be active competitors in the specific technological area, and competition is manifested in patents. Even when a patent granted to one firm compliments a patent held by another, a long term competitive threat can exist, since both have related technological expertise that can be developed in a variety of ways. The focus here is on substitutability within a technology. The model (Figure 1) brings together those factors that: (1) Have been identified in previous IO studies of innovations as affecting the amount of research activity in an industry; and (2) are measurable in the patenting process. The term Patent activity refers to the number of patents (NUMPATS) granted within a specific technological area. It is a measure of research output. Previous studies of innovations have consistently found a strong positive rela-

INumber

of competitors

tionship between industry R&D input and the rate of industry innovation. In addition to the number of patents granted, innovation output measures have also included sales volume from new products, total number of inventions, and the probability of innovation success [13, 14, 151. Although they establish an important and fundamental relationship, these studies offer little insight into the dynamic, competitive nature of industry research, particularly as it pertains to a specific technological area. It is uncertainty regarding the factors that contribute to patent activity in specific technological areas that motivates this article’s focus on the structure of “industry” research within each area. RESEARCH

QUESTIONS

Generally, the number of competing firms is positively related to the total number of innovations observed [16]. Under the simplest economic assumptions, the greater the number of firms operating in a technological area, the greater the competition in that area. This assumption is based on the theory that although an increase in the number of competitors increases research risks, firms will pursue

\ Technological

I

IResearch

concentration

I 1

I

Lead time

Technological

complexity i

Patent

Izizq

focus FIGURE 1.

Conceptual

model.

259

more research despite the increased risks as long as they accrue acceptable R&D returns [16]. Thus, competitive industries tend to force continued innovation. Not everyone agrees with this approach. Some economists argue that as the number of competing firms increases, the amount of profits available to each firm decreases [17]. Lower profits mean fewer resources available for research. As profits continue to fall, each firm reduces its research effort until the industry’s total research effort eventually declines [18, 191. But despite arguments to the contrary, the empirical evidence supports a positive relationship between the number of firms and the level of research activity. The claim that the number of firms is positively related to the number of patents appears tautological, given the obvious fact that each new patenting firm increases the number of patents. But multiple patent filings by a single firm is a common practice. Research activity within a patent subclass can be attributed to one or many firms. As a result, the relationship between the number of firms and the amount of patent activity may not be as strong as initially thought. The inclusion of the variable in the model not only recognizes the positive relationship observed but also allows the strength of the variable to be tested relative to other variables modeled.

Question 2: Will the amount of patent activity in a technological area increase at a decreasing rate as the level of research concentration (RCR4) increases? Being first to market with a product can be an important step toward market success. Generally, pioneers tend to retain superior market shares despite the arrival of late competitors [24, 25, 261. Narin and Smith [27] have shown that market share has a lagged and positive correlation with a company’s share of total relevant patents. Research activity prior to commercialization would seem to be a critical precursor to a pioneering advantage. If potential rivals are willing and able to respond to a competitive threat, it is reasonable to expect that a new entrant in a technological area would attract attention and subsequently stimulate research activity. Marketing research (cited above) suggests the shorter the lead time between a technological pioneer and the first competing firm in a technological area, the greater the total patent activity. The lack of competitive entry may reduce the pioneering firms R&D activity, either because the pioneer can exploit an early monopoly position or because it is simply not pressured to innovate. In either case, both the pioneering firms patent activity and total patent activity in the technological area are diminished. Thus the third question:

Question I: Does a greater number of competitors (NUMCOMP) result in more patent activity in a technological area?

Question 3: Does a longer competitor lead time (LTIME) lower the patent activity in a technological area?

The degree to which the industry is dominated by a few large firms can affect the amount of research activity observed. Some suggest that a more concentrated industry provides greater opportunities to extract profits for the purpose of financing future innovations, resulting in a positive relationship between concentration and research activity [12, 191. Others argue that an industry dominated by a few large firms will be less innovative, preferring instead to extract rents from their current products [20, 211. Recent studies based on a large number of industries indicate that both effects may be present. Industry concentration has been found to have a positive effect on the number of industry innovations, but the effect decreases and becomes negative at high levels of concentration [12,22,23]. The current study substitutes research concentration for industry concentration. If concentrated technological power is similar to concentrated industry power, then the relationship between research concentration and patent activity should follow a pattern similar to that found between industry concentration and industry innovations. An inverted “II” relationship between research concentration and patent activity is hypothesized here.

Though not explicitly an IO variable, the extent to which firms focus their research in a specific technological area may affect the amount of patent activity in the area. Technological focus is difficult to measure at the firm level, but it can be important in speeding research activity [28]. Some authors have called for the establishment of core areas of expertise [29]. It appears that technological focus and the development of a few technological competencies should lead to a competitive advantage [30]. If core areas of expertise can be developed and fine-tuned, useful patentable innovations seem more likely. Diversification of R&D across broad technology boundaries may dilute efforts and diminish the ability to reach the technological mass needed to facilitate further research activity. Alternatively, if knowledge resources can be leveraged, research synergies across technological areas may be possible. Studies have considered the relationship between R&D spending and various research and corporate diversification measures [12,3 1,321, but their results were inconclusive. The lack of evidence regarding the leveraging of technical knowledge may stem from the difficulty of measuring

260

Research activity leads to patent activity. technological focus. The current study provides a measure of technological focus and tests its impact. Question 4: Will greater technological focus (TFOCUS) in a specific technological area result in higher patent activity in that area? A final variable to be considered is the degree of complexity in the technological area. This characteristic is not part of the structure of industry research; rather, it is an inherent part of the technologies used in an industry. Products containing a greater number of technologies face greater risks, and managers may not be willing to tolerate the greater uncertainty [33]. Uncertainty increases because more information must be acquired and usefully applied, a more complex development process is involved, and far greater sophistication in the synthesis is required [34]. Studies using different measures of complexity found the more complex the technology, the longer the waiting time for product introductions and first product shipments [35,36]. The net effect is that technologically complex products require greater coordination of technologies, information, and processes, which results in lowered research activity. Question 5: Will greater technological complexity (ICMPLX) lower the patent activity in a technological area?

PATENT DATA BASE Every patent granted in the United States is assigned to one or more patent class and subclass. These assignments are made by the patent examiner based on information from the applicant and reflect the examiner’s decision as to the technological area(s) most affected. It is important to note that the classification is based on technological area, not industry. The U.S. patent classification scheme consists of approximately 360 classes and about 100,000 subclasses [9], although the numbers change as new classes and subclasses are added. A knowledge of the nuances of the classification scheme is important to understanding how the sample was chosen for the current study. Each patent class represents a group of related technol-

ogies. The class is further divided into subclasses representing greater levels of technological specificity. Some patent classes, such as class 354: Photography, appear to correspond to identifiable industries. Others, such as class 116; Signals and Indicators, appear to be more closely associated with technological functions. The difference reflects the fact that some technologies spawned a single industry, whereas those more general in nature have been used in many industries. A competitive threat can come from almost any technological area (or patent subclass), but managers tend to be concerned with developments in areas known to be relevant to their overall industry. As a result, the current study uses only subclasses drawn from one patent class, class 354: Photography. Each subclass has some relationship with the overall industry of photography, but the technological problems of one subclass (for example, automatic camera focusing) are different from those of another (such as automatic exposure control). Selecting subclasses from a single patent class also controls for interclass variation, a potential mediating factor not a part of the current study. The photography category is interesting for a variety of reasons. First, photography ranks fifth among U.S. industries in the percentage of net sales spent on R&D [12]. Second, researchers in the photography industry show a propensity to patent their technological innovations. The Eastman Kodak Company is a leader among U.S. firms filing patent applications and has helped pioneer research on strategic patenting [37]. Third, photography R&D is a microcosm of global competition, with 57.6% of all U.S. patents in this class held by Japanese firms [38]. The availability of patent information is an important sampling consideration. Because subclasses of patents granted prior to 1969 are not recorded on the electronic database available from the USPTO, only those subclasses with at least 50 % of the patent activity occurring since 1969 were chosen. Without this criterion, subclasses with few measurable data points would be included in the sample. The 50% criterion kept the percentage of patents in each subclass available for analysis high (78.3 %), and provided a sufficient sample size (n = 181). A final step in sample selection was to eliminate patents held by individual inventors. Previous research suggests 261

that these patents, as opposed to those held by corporations, are relatively unimportant in the competitor analysis context [9]. OPERATIONALIZATION

OF VARIABLES

Measuring variables using patent data is relatively easy because of its accessibility. Table 1 shows the operationalization of each variable. Since the model is a study of patent activity at the subclass level, and since each subclass contains data for patents assigned to that subclass, the actual unit of analysis is the assignment of a patent to a subclass. The operationalization of all variables with the exception of lead time was accomplished using the CD-ROM electronic database known as the Classification and Search Support Information System (CASSIS), which is available from the USPTO or public libraries serving as patent depositories. The measurement period, with the exception of lead time, was from January 1969 to August 1990. Since lead time begins with the first patent in the subclass, in some cases the lead time measurement period was prior to 1969. In those cases, the variable was measured using hard copy data from a patent depository library.

TABLE 1 Variable Definitions

Variable NUMPATS

NUMCOMP

RCR4

LTIME

TFOCUS

TCMPLX

Measurement Number of patentsfiled in a sublcass during a specific period of time Number of firms patenting in the subclass Share of patents in subclass held by four top firms Time period between when initial firm is granted a patent in subclass and when second firm is granted a patent in the same subclass Percent of each firm’s total patents filed in subclass averaged across all firms Total number of subclasses the average patent in subclass is assigned to

Construct Being Measured Amount of patented research in a specific technological area Number of competitors in the technological area Degree of research concentration within the technological area Competitor lead time in technological area

Level of technological focus of firms conducting R&D in the technological area Degree of product complexity

Dejnirions: “technological area” refers to a specific patent subclass, “subclass” refers to the particular patent subclass under investigation.

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RESULTS Table 2 provides the regression results. Five of six independent variables are significant at the 0.10 level. The model has an unadjusted r2 of .7228. The results show that a greater number of competitors does increase patent activity in a technological area (Question 1). This finding supports two important aspects of the innovation process. First, even in narrowly defined industries, an increasing number of competitors increases the risk to firms in the industry, thereby increasing the need to find greater competitive advantage. As the need for competitive advantage increases, so does the firm’s tendency to innovate. Second, by using patent data the model assumes an environment that allows a firm to appropriate the benefits of its innovations. The positive relationship between the number of competitors and the number of patents granted is strong both in spite of, and because of, the monopoly protection provided through patent protection to innovating firms. The regression results also indicate that patent activity in a technological area increases at a decreasing rate as research concentration increases (Question 2). Whereas research concentration, RCR4, has a positive and significant effect on the dependent variable, RCR42 is negative and significant. This result is consistent with recent empirical studies in the economics literature and supports the notion that maximum research activity occurs at moderate levels of research concentration. The coefficient for the lead time variable is negative, but it is not statistically significant; therefore, the answer to Question 3 must be “No.” A shorter time between entry of the pioneering firm and the first competing firm does not appear to generate a greater number of patents in the subclass. It is possible that a later entrant may introduce

TABLE 2 Multiple Regression

Results: Full Model

Independent Variable

Coefficient

(Constant)

- 179.5554

t-Statistic -3.958

NUMCOMP

4.7516

19.328

RCR4

5.9214

5.742

RCR42 LTIME

-0.0331 - 1.0397

-4.070

Significance .0001* .0001* .OOQ1* .OOQ1*

-0.662

.5090

TFOCUS

-66.9789

-2.030

.0439*

TCMPLX

-20.1192

-4.004

.0001*

f-sfutisfic = 75.632 (significance * Significant at the 0.10 level.

= O.OOOl), R* = .7228.

Patent monitoring can help guide research activities. technology that prompts a pioneering firm to defer its own research activity and await further developments. The nonsignificant result may also be a function of the way that variable is measured. The initial univariate analysis of the variable indicated an extremely skewed distribution. The square root of the measure was used in an attempt to mimmize the effect of skewness, with only marginal improvement in the distribution. Future research will need to study both an alternative measure of the variable and theory of the pioneer/follower relationship. The answer to Question 4 is also “No.” But unlike Question 3, the significant negative finding for Question 4 indicates that greater technological focus will actually reduce the amount of patent activity in a technological area. The result supports the view that being too technologically focused will diminish a firm’s research output. The relationship between technological complexity and the amount of patent activity is also negative and significant. Therefore, the answer to Question 5 is “Yes.” The negative relationship supports the argument that technologically complex innovations require more time. In the patent data environment, this means the presence of technologically complex patents will slow the number of patents granted. CONCLUSIONS The current model suggests a means of monitoring, modeling, and perhaps predicting research activity in patented technologies. Though the theoretical underpinnings come from empirical work conducted at a broader industry level, the database is technologically specific and easily accessible. The overall findings suggest that a moderate number of competitors will be needed to maintain patent activity in a technological area as technological complexity increases. This conclusion is based on the relationships between patent activity and the number of competitors on the one hand, and technological complexity on the other. The findings regarding research concentration and technological focus suggest that too few firms or firms that are

too technologically focused will inhibit research output. In other words, research activity is maximized when there is a moderate number of competing firms with each having a broad technological base. MANAGERIAL

IMPLICATIONS

The primary managerial implication of the current research is the potential for improved understanding of competitive relationships based on technological advantage. As discussed earlier, the speed of technological change increases the need for reliable information on evolving technologies. Recommending acquisition targets, managing product portfolios, and analyzing evolving technologies are important strategic managerial functions. The current model gives managers the ability to measure and model the number of technological competitors, the degree of research concentration in the technology, the technological focus of competing firms, and the level of technological complexity in the technology. With the current model and available patent data, managers have an information database regarding those technology areas that are most likely to evolve quickly and those that are changing more slowly. Development of industry research activity models can provide competitive benchmarks. Managers can then compare their firm’s technological research activity with these benchmarks. If their firm appears to have a technological edge, they can prepare to exploit the relative advantage. If not, managers can take defensive measures using current products and technologies. In summary, the current research contributes to the manager’s ability to identify competitive threats before they translate into actual changes in the market.

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