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Factors Differentiating the Commercialization of Disruptive and Sustaining Technologies Suleiman K. Kassicieh, Member, IEEE, Steven T. Walsh, Member, IEEE, John C. Cummings, Paul J. McWhorter, Alton D. Romig, and W. David Williams

Abstract—The nature of disruptive and sustaining technologies is sufficiently different to require different activities for the commercialization of these technology categories. Few theorists have developed conceptual schemes about the different methods of commercializing these technologies. The authors take the first steps in investigating these differences by contrasting firms that commercialize disruptive technologies with those that commercialize sustaining technologies. They reveal major differences and analyze these in terms of four major commercialization components: product realization, revenue generation, research support, and market potential. Several hypotheses regarding size of the firm, its financial risk profile, and its R&D strategy are utilized. Index Terms—Disruptive technology, technology commercialization, technology management factor analysis.

firms utilize when commercializing disruptive technologies. To test these hypotheses, we use one of the emergent and potentially disruptive technologies in which Sandia National Laboratories are involved. This nascent disruptive technology area is micro-electro mechanical systems (MEMS), sometimes referred to as Microsystems, or Top Down Nanotechnology. We survey a number of companies that have investigated Sandia’s technological discoveries for potential use in an industrial capacity. The survey will focus on the movement of the research findings from the laboratory into the market place and all of the problem areas that disruptive technologies face in this arena. The survey data will be described with results and conclusions reported.

I. INTRODUCTION

II. DISRUPTIVE TECHNOLOGIES DEFINED

LTHOUGH it is widely believed that the two major categories of technologies are disruptive and sustaining, few theorists (Tushman et al. [34], Bower and Christensen [4], Veryzer [37]) have demonstrated that firms utilize differing methods to commercialize these different technologies. Traditionally, commercialization activities were treated as similar whether the new technology incrementally improved an existing product, process, and service or disruptively introduced a new technology that had a major effect on the market and/or customer behaviors and benefits (Usher [36], Mansfield [21]). This paper seeks to provide an empirical basis for these differences. This paper differentiates between the commercialization activities of disruptive and sustaining technologies. It tests differences in activities and decision-making processes that affect the commercialization efforts of these technologies. This study helps to provide a basis for a commercialization decision framework so as to help R&D organizations move scientific discovery to a commercial arena. It also supports commercial organizations in defining a methodology for analyzing their involvement in bringing disruptive technologies into successful discontinuous innovations. We test several hypotheses, which are designed to highlight firm differences in commercializing disruptive and sustaining technologies. We will highlight activities and factors that

Disruptive technologies are scientific discoveries that break through the usual product/technology capabilities and provide a basis for a new competitive paradigm, as described by Anderson and Tushman [2], Tushman and Rosenkopf [35], and Bower and Christensen [4]. Discontinuous innovations are products, processes, and/or services that provide exponential improvements in the value received by the customer much in the same vein (Walsh [39], Lynn et al. [20], and Veryzer [37]). Walsh and Linton [41] reported on the definitions used by different authors to describe the business strategy focus they used to define disruptive technologies. These definitions are classified by a number of business strategy parameters used to describe disruptive technologies. Disruptive technologies and discontinuous innovations present a unique challenge and opportunity for R&D organizations seeking to decide on their R&D investments and for manufacturing organizations devising plans for their commercialization efforts and meeting the challenge to reinvent the corporation. These technologies do not have a proven path from scientific discovery to mass production and, therefore, require novel approaches although they are the wellspring of wealth creation and new competency generation for the firms that introduce such innovations. Many firms, especially the larger ones, seem reluctant to familiarize themselves with these technologies quickly. The trend seems to be that these firms prefer to react to a proven disruptive technology that has changed the product market paradigm. As a result, the community of corporate customers does not readily accept them until they are proven, an event that usually means corporate customers are late entries into the market. Tushman et al. [34], for example, presented the idea of a technology cycle where technological discontinuities, sub-

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Manuscript received December 2000; revised July 2002. Review of this manuscript was arranged by Special Issue Editor B. A. Kirchhoff. S. K. Kassicieh and S. T. Walsh are with the Anderson Schools of Management, University Of New Mexico, Albuquerque, NM 87131 USA. J. C. Cummings, P. J. McWhorter, A. D. Romig, and W. D. Williams are with Sandia National Laboratories, Albuquerque, NM 87185 USA. Digital Object Identifier 10.1109/TEM.2002.807293

0018-9391/02$17.00 © 2002 IEEE

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stitution of technologies, dominant designs, and incremental change are part of an iterative technology cycle. This cycle implies that firms need to have organizations that have dual responsibilities: maintain the current production system with small incremental changes while at the same time look for the major breakthroughs. The “ambidextrous” organization allows the firm to bring in the resources while at the same time building new products. Anderson and Tushman [2] had developed the idea of discontinuities and their relationship to dominant designs. Glasmeier [11] presented the effect that a new discontinuous innovation, quartz technology, had on the mechanical movement Swiss watch industry.

technologies. Additional evidence that firms require more than continuous improvement as a design and manufacturing strategy is offered by Morone [25]. He found that successful Japanese and U.S. firms in different industries were more similar to each other than to unsuccessful firms in the same industry. The successful firms, regardless of country of origin, achieved a competitive advantage over rival firms based on a combination of incremental and discontinuous innovation. However, none of these develops a strong empirical basis that demonstrates these differences. Therefore, we provide a basis herein. IV. FIRM ACTIVITY AND DISRUPTIVE TECHNOLOGY

III. COMMERCIALIZATION OF DISCONTINUOUS INNOVATION BASED ON DISRUPTIVE TECHNOLOGIES Commercialization has not been totally overlooked in the management of technology literature. Several examples make this clear. Christensen [6], for example, states that largest firms neglect discontinuous innovations and focus their resources on incremental change or continuous improvement. He presented the case of the hard drive manufacturers and how incremental innovations and sustaining technologies were not sufficient for survival when new disruptive technologies were leapfrogging the price/performance parameters of these incremental innovations. Rice et al. [30] reported on a joint project with the Industrial Research Institute (IRI) where 11 projects in nine companies were designated as “breakthrough” technologies. The focus of the project was to understand the management of high-risk projects associated with commercializing discontinuous innovations. Projects with a five to ten times improvement in performance, 30%–50% reduction in cost, and/or new-to-the-world performance were defined as “breakthrough” discontinuous innovations. An example of the companies and products used in the project is General Electric and its digital X-ray. The projects had common mechanisms such as definition of a “holy grail,” establishment of venture boards, internal requests for proposals, and scanning for ideas by groups and individuals. Kaplan [13] presents strategies to take advantage of disruptive technologies. These strategies include radical cannibalism by replacing one’s own successful products with new products that represent a significant value increase for customers. Another strategy is competitive displacement where you replace your competitors’ products with new significantly higher valueadded products. The other two strategies are industry genesis where you start new industries and market invention where you create new demand. Others have contrasted discontinuous innovation with continuous innovation. Two examples are well known. Florida and Kenney [9] argue that prior to the 1980s, the U.S. was noted for the ability of its firms to develop new ideas and new products. The 1980s, however, focused attention on continuous improvements due to the disappointing performance of U.S. firms in technology intensive markets such as consumer electronics, robotics, automobiles, and semiconductor memories. This focus shifted attention from the disruptive technologies that had helped the U.S. in leading the world in new breakthrough

Fig. 1 uses three distinct areas of change to define disruptive technologies. These areas are as follows. 1) Change in technology/product paradigm: these changes impact the decisions a firm makes to commercialize a particular product. 2) Change in market structures: these changes result in different suppliers in the market and different outputs among the remaining suppliers. 3) Change in customer benefits: users/adopters have to change their behavior in order to benefit for the use of the innovation. Fig. 1 lists the different authors who have described the effect of disruptive technologies on these three areas of change. These changes point to the need for a new decision framework for commercialization decisions. An appropriate decision framework helps R&D organizations move scientific discovery to a commercial arena. It also supports commercial organizations in defining a methodology for analyzing their involvement in discontinuous innovations. This decision framework is presented next. V. SOURCES OF DISRUPTIVE TECHNOLOGIES: R&D ORGANIZATIONS Sandia is a world class R&D facility that faces the challenge of managing rapidly changing and interactive technologies and products. These technologies, although “high tech” in nature, are not always disruptive in nature. Herein, we divide them into sustaining technologies and disruptive technologies. Sustaining technologies follow a more continuous improvement marketfocused process (Walsh and Kirchhoff [17]) and are applied to internal and external customer problems that intensify rather than create new lab competence. Sustaining technologies can be planned according to a technological roadmap and add value to an established industrial value chain (Walsh and Elders [19]). Disruptive technologies, on the other hand, follow a more discontinuous innovation path (Walsh and Kirchhoff [17]) requiring a market-development or expeditionary marketing approach (Prahalad and Hamel [28]) rather than the marketfocused approach (Porter [29]) utilized more effectively with sustaining technologies (Linton [19]). When deriving value from these technologies, the exact placement of the disruptive technology in an existing industry value chain is not clear. Technological roadmaps are very hard to construct for these

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Fig. 1.

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Disruptive technology definitions focused on technology/ products/ markets/ customers.

technologies since the contribution to the industrial value chain is murky and the products are not so obvious. Traditional market focus forces provide little aid in these areas. Most firms, when faced with creating competitive advantage from disruptive technologies, revert back to an internally driven approach which can be successful but has a history of generating marketing myopia, not-invented-here syndrome, and the like. Sandia, however, perhaps due to the nature of the National Labs, where competency generation and creation is the more natural stock and trade has initiated what we call a market development approach. Since the market-focused approach and the internally driven approach have been around and are easily applied to technologies where markets and customers exist, a new approach is needed for disruptive technologies. This approach needs to provide companies, in many application areas and totally unrelated fields, with a way to experiment with the new technologies to determine how they can assist in developing new products that diverge from the traditional demand for the company’s products. Many articles suggest differences in firm typology [16] and firm activity [20] when commercializing disruptive technologies. These differences depend on many factors and some are developed as follows. a) Size of firm commercializing the technology: Small entrepreneurial firms have been a driving force behind the commercialization of disruptive technologies. Birch [3], Kirchhoff [16], and Reynolds [32] indicate that highly innovative small firms create a majority of net new jobs in the U.S. These firms are more agile and are better able to deal with uncertainty than larger firms. Large firms have also responded to the challenge of starting new areas of business. Cooper and Smith [7] describe how firms

that have a well-established product behave when a new technology threatens the dominance of their established product. In some cases, they conclude that the establishment of a new division to handle the new technology is warranted. Christensen [6] points out Hewlett Packard’s experience with the ink jet and the laser jet where the two competing technologies managed by two separate divisions netted a positive result. Refer to Fig. 2 for the different details. b) Technology Source: Kassicieh and Radosevich [14] noted that technology transfer and commercialization of new products from public-sector research organizations are more likely to find their way to the market with more channels of communications. This principle undoubtedly applies to disruptive technologies since the high level of uncertainty attached to new-to-the-world technologies requires trial in many different industries and many different products. Kirchhoff and Walsh [17] state that many times these disruptive technologies are exogenous both to the firm and to the industry they are utilized in. We provide these in Fig. 3. c) Risk of Involvement with New Technology: The risk taken by firms commercializing disruptive technologies is far greater than the risk taken by firms working on sustaining market-driven technology commercialization. Firms who are not succeeding financially are more apt to take a chance on the disruptive technologies. (See Fig. 4.) VI. COMMERCIALIZATION MODELS Commercialization models depend on a variety of issues that define a market focus for product development or on

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Fig. 2. Market approach based upon firm size and technology type.

Fig. 3. Market approach based upon technology source and type.

Fig. 4. Market approach based upon financial success, risk, and technology type.

a technology development perspective that develops new markets. These two foci depend on the existence of many elements as described by various authors including Kassicieh and Radosevich [14], Von Hipple [38], and Lynn, et al. [20]: 1) scientific discovery; 2) applications; 3) products; 4) government support/buyers; 5) commercial support/suppliers/buyers; 6) distribution channels; 7) research support for new discoveries; 8) research support for new applications; 9) research support for new products; 10) buyers/market; 11) real market growth; 12) perceived/potential market growth. This paper will test how these parameters influence the planning of disruptive technologies and the creation of new products in the market place.

VII. HYPOTHESES The purpose of this study is to examine the behavior of firms as it relates to the commercialization of sustaining disruptive technologies and determining the differences between the two groups. Responses to the questionnaire provided data for a discriminate analysis that sought to find a model that effectively predicts these differences. This analysis will help us in focusing

commercialization efforts on certain types of firms for different areas of technology and different situations. It allows a descriptive analysis of the commercialization activities of firms but can lead to a prescriptive set of recommendations that change the way firms examine new technologies. In this study, we have respondents from two populations that differ in the character of the technologies chosen for commercialization. To test for differences between the two groups, we tested for separate hypothesis developed from the literature and bounded by our survey responses. All of the hypotheses utilize product realization, revenue generation, research support, and market potential as variables to one extent or another. We developed these variables from product realization efforts by Lynn, et al. [20], Veryzer [37], and others. We supported this hypothesis from revenue generation input from Kaplan [13], Moore [24], and others. The hypothesis was fortified by market potential literature developed by Linton [19], Moore [24], and others. Finally, we developed the research support portion for this hypothesis literature from Kassicieh and Radosevich [14] Tushman, et al. [35], and others. A. Hypothesis 1 The sustaining technologies group differs from the disruptive technology group in the four factors of importance: product realization, revenue generation, research support, and market potential. Here, we utilize the literature that categorizes technology by its commercial intensity such as efforts by Schumpater [33], Anderson and Tushman [2], Walsh and Linton [41], and many others in conjunction with the aforementioned literature used to

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develop our four factors of product realization, revenue generation, research support, and market potential. B. Hypothesis 2 The large firms differ from the small firms in the four factors of importance: product realization, revenue generation, research support, and market potential. The development of this hypothesis relies heavily on the small firm literature from authors such as Kirchhoff [16], Birch [3], Rice, et al. [30], and many others as well as the aforementioned literature used to develop our four factors of product realization, revenue generation, research support, and market potential. C. Hypothesis 3 Firms with a large internal R&D function (large R&D group within the firm points to an internal source of innovation) differ from firms with a small R&D function (therefore external sources of innovation) in the four factors of importance: product realization, revenue generation, research support, and market potential. Here again, we utilized the four-factor literature base supplementing it with the efforts from Kassicieh and Radosevich [14], Carroad and Carroad [5], and many others. D. Hypothesis 4 Firms with good financial and market performance over the last few years (good financial or market performance leads to a tendency to take less risk on new disruptive technology) differ from firms with poor financial and market performance in the four factors of importance: product realization, revenue generation, research support, and market potential. Here again, we developed much of our hypothesis from the four-factor literature base and Kaplan [13], Kassicieh and Radosevich [14], and many others. The responses were also classified according to different combinations. The sustaining technologies group (ST) and the disruptive technologies group (DT) could be further classified into small or large firms (SF or LF), firms with external or internal sources of innovation (ExI or InI), and firms who have performed well or poorly in financial/ market results (GR or PR), and who are apt to take more or less risks, so that we now have four groups in each category. 1) Major Hypothesis 1: Large ST firms, Small ST firms, Large DT firms, and Small DT firms differ in the importance placed on the four factors (product realization, revenue generation, research support, and market potential) related to commercialization. 2) Major Hypothesis 2: ST firms with internal sources of innovation, ST firms with external sources of innovation, DT firms with internal sources of innovation, and DT firms with external sources of innovation differ in the importance placed on the four factors related to commercialization. 3) Major Hypothesis 3: ST/GR, ST/PR, DT/GR, DT/PR differ in the importance placed on the four factors related to commercialization.

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VIII. METHODOLOGY A questionnaire that queried respondents about their company and the importance of several areas in commercialization was sent to a sample from two populations. Both populations were firms that have collaborated with Sandia National Laboratories (Sandia) on an innovation. The first population worked with Sandia in the area of MEMS, which is one of the disruptive technology areas. The second population worked with Sandia on other technologies that are sustaining or improving the current level of technologies used in the firms’ products or services. While different inventions in these two areas represent varying degrees of entrepreneurial opportunity, we selected only those where a commercial firm showed a strong interest. The same survey instrument was used for both groups. The disruptive technology commercialization group (DT group) consists of individuals representing organizations that had participated in one of Sandia’s MEMS commercialization activities. Sandia offers training, design software, training in MEMS manufacturing, and prototyping facilities for use by firms with an interest in MEMS technology. This group is made up of 174 participants. The sustaining technology commercialization group (ST group) is made up of managers and technologists from firms that have worked with Sandia in a variety of joint research and development agreements but not MEMS. This second group is made up of 207 individuals. The surveys were sent to these individuals with e-mail and phone follow-up to increase the response rate. Seventy-two ST group responses were received (35% response rate) and 59 DT group responses (34% response rate). The response rate is substantial given the sensitivity of the information. The questionnaire consisted of questions about the firm: its size; the number of locations; its activities in R&D, design, manufacturing and sales, and the number of employees in each one of these areas, and the importance of the two foci parameters listed earlier. The survey instrument consisted of 54 questions designed to capture data about several variables. Questions were derived from three sources: 1) the authors’ experiences with laboratory spin-offs over the last two decades; 2) a pilot study; and 3) the literature on commercialization cited above. The survey allows us to deal with the firms in many dimensions: a) sustaining or disruptive technologies; b) small and large firms; c) firms with large R&D functions where the source of the firm’s product and process innovations will be internal as opposed to firms with small or no internal R&D function that depend on external sources for innovations in products or processes; d) firms who have performed well in financial returns and/or market share versus firms who have not done well in these dimensions. These firms were asked about the importance of the following variables using a ten-point scale with semantically anchored end points: 1) innovation; 2) applications;

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TABLE I T-TEST OF DIFFERENCES BETWEEN FACTOR MEANS FOR THE SUSTAINING TECHNOLOGIES AND DISRUPTIVE TECHNOLOGIES GROUPS

3) 4) 5) 6) 7) 8) 9) 10) 11) 12) 13) 14) 15) 16)

existing products; government buyers; commercial buyers; distribution channels; research support for applications; research support for new products; market growth potential; acquisition of external innovations; investment in research; product development for revenue generation; process development for revenue generation; product families for revenue generation; speed and timeliness of new processes; speed and timeliness of new products.

Factor analysis was run for these 15 variables using principal components with varimax rotation. These variables were reduced to four factors with Eigenvalues greater than 1 and the reliability was measured with Cronbach’s alpha. 1) Product Realization: The following variables were included in this factor: the importance of acquisition of external innovations, investment in research, process development for revenue generation, speed and timeliness of new processes, and speed and timeliness of new products. This factor has a reliability of 0.7412. 2) Revenue generation: The following variables were included in this factor: the importance of buyers, product development for revenue generation, product families for product generation, and new products. This factor has a reliability of 0.7640. 3) Research Support: The following variables were included in this factor: the importance of innovation, government buyers, research support for applications, and research support for new products. This factor has a reliability of 0.7113. 4) Market potential: The following variables included in this factor: the importance of applications, existing products, distribution channels, and market growth potential. This factor has a reliability of 0.7089.

To ensure the reliability of the survey instrument, Cronbach’s alpha for the 15 variables is 0.7234. Nunally [27] indicates that a reliability measure of 0.70 or higher is acceptable indicating the reliability of the survey instrument. IX. STUDY RESULTS We conducted statistical tests for the each one of the hypotheses. In each case, the t-test was conducted to test for differences between the mean responses for the four factors. We provide our four hypotheses and results here. A. Hypothesis 1 The sustaining technologies group differs from the disruptive technologies group in the four factors of importance: product realization, revenue generation, research support, and market potential. Here our hypothesis that firms focusing on sustaining technologies differ from those that focused on disruptive technologies was supported. Our analysis of the two groups by means of a t-test highlights the differences between the mean responses for the four factors. We provide the t-test analysis in Table I. B. Hypothesis 2 The large firms differ from the small firms in the four factors of importance: product realization, revenue generation, research support, and market potential. Here, our hypothesis that large firms focusing on disruptive technologies differ from small firms focusing on disruptive technologies was not supported at least along our four factors. Our analysis of the two groups by means of a t-test demonstrates no significant differences between the mean responses for the four factors. We provide the t-test analysis in Table II. C. Hypothesis 3 Firms with a large internal R&D function (large R&D group within the firm points to an internal source of innovation) differ from firms with a small R&D function (therefore, external

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TABLE II T-TEST OF DIFFERENCES BETWEEN FACTOR MEANS FOR THE SMALL AND LARGE FIRMS

TABLE III T-TEST OF DIFFERENCES BETWEEN FACTOR MEANS FOR THE INTERNAL SOURCE OF INNOVATION GROUP AND THE EXTERNAL GROUP OF INNOVATIONS GROUP

sources of innovation) in the four factors of importance: product realization, revenue generation, research support, and market potential. Here, our hypothesis that firms focusing with large internal R&D functions differ from firms with small R&D functions was not supported. Our analysis of the two groups by means of a t-test demonstrates no significant differences between the mean responses for the four factors. We provide the t-test analysis in Table III. D. Hypothesis 4 Firms with good financial and market performance of the firm over the last few years (good financial or market performance leads to a tendency to take less risk on new disruptive technology) differ from firms with poor financial or market performance in the four factors of importance: product realization, revenue generation, research support, and market potential. Here, our hypothesis that firms with good financial and market performance differ from firms with poor financial or market performance was not supported. Our analysis of the two groups by means of a t-test demonstrates no significant differences between the mean responses for the four factors. We provide the t-test analysis in Table IV. X. DISCUSSION We demonstrated in Table I that firms interested in commercializing sustaining technologies differ from firms that are in-

terested in commercializing disruptive technologies in three of the four factors. The existence of revenues, the availability of research support, and the presence of potential markets were all significant factors in their decisions to pursue technology development and commercialization. Sustaining technologies firms placed more importance on new products and markets than disruptive technologies firms. Disruptive technologies firms placed more importance on research support. These results are intuitively appealing and follow the logic that has been advanced by many authors previously. We could not find significant differences between large and small firms as portrayed in Table II. The fact that no significant differences are indicated is counterintuitive given to much of the commercialization literature which has stressed the importance of small entrepreneurial firms in the innovation process. This result might indicate that large firms have realized that they need to examine new disruptive technologies and commercialize them when the opportunities are available. Another possible explanation is that the small firms in our study differ significantly from many other small firms (i.e., they have more money than many small firms and act like large firms). Another plausible explanation is that large firms realize the importance of disruptive technologies and indicate its importance but usually do not proceed to commercialize the technologies due to many internal structural issues present in those firms. Another explanation might be that large and small firms do differ but not along the factors we have proposed. Finally, it is hard to discern if the

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TABLE IV T-TEST OF DIFFERENCES BETWEEN FACTOR MEANS FOR THE FINANCIALLY WELL-PERFORMING FIRMS GROUP AND THE FINANCIALLY POOR-PERFORMING GROUP

TABLE V FACTORS ANOVA AND FACTOR MEANS AND STANDARD DEVIATIONS FOR TECHNOLOGY TYPE AND FIRM SIZE

large firms are gate keeping these technologies or actually commercializing them. Nevertheless, this is a very interesting result that might indicate that a change has resulted from all of the literature that prescribes the “ambidextrous” organization. We could not find significant differences between firms that have large internal R&D functions and firms that depend on external sources as portrayed in Table III. This indicates that firms may have been diligent in pursuing new technologies in both sustaining and disruptive areas whether they have emanated from within the organization or from outside sources. Another plausible explanation is that many firms realize the importance of disruptive technologies and indicate that many times they are found exogenous to the firm as indicated in much of the management literature. We could not find significant differences suggesting that wellperforming firms (financially and/or in market share) have been placing more importance on the innovation process and on new products than firms that have not done well financially as portrayed in Table IV. This is again counterintuitive on two fronts because it has been argued previously that firms that are not doing well financially will take more risks or that well-performing firms have inherently better innovation processes.

We further examine and discuss different aspects of firms interest in disruptive technologies through further sets of hypotheses focusing on separating our groups according to size, sources of innovation, and financial performance but also classifying them as disruptive technology firms or sustaining technology forms to further understand the differences between these two types of firms. Table V shows the ANOVA test (Neter et al., [26]) was run to test for differences among the four groups of firms: 1) small firms interested in sustaining technologies; 2) large firms interested in sustaining technologies; 3) small firms interested in disruptive technologies; 4) large firms interested in disruptive technologies. Significant differences were found in two factors: revenue generation and market potential. This result supports the results shown in Table I with the same interpretation. Table VI examines the differences between each one of the four groups. Significant differences at the 5% and 10% level existed among many of the groups. 1) Small and large sustaining technologies firms behaved similarly.

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TABLE VI FACTOR HYPOTHESES TESTING

TABLE VII FACTORS ANOVA AND FACTOR MEANS AND STANDARD DEVIATIONS FOR TECHNOLOGY TYPE AND INTERNAL/EXTERNAL SOURCE OF INNOVATION

2) Small firms in sustaining and disruptive technologies differed on the importance of the existence of potential markets. Disruptive technologies firms usually know that the markets have to be created from their work and that they do not exist prior to that work. 3) Small sustaining technologies firms and large disruptive technologies firms seem to be similar. 4) Small firms in disruptive technologies differed significantly from large sustaining technologies firms as to the importance of potential markets. The same analysis as in ii) above. 5) Large sustaining technologies firms differed from large disruptive technologies firms in placing importance on revenue generation and potential markets. 6) Large and small disruptive firms acted similarly. Table VII indicates the differences among four groups: 1) firms that depend on external sources of innovation that are interested in sustaining technologies; 2) firms that depend on internal sources of innovation are interested in sustaining technologies; 3) firms that depend on external sources of innovation that are interested in disruptive technologies; 4) firms that depend on internal sources of innovation are interested in disruptive technologies.

and and and and

Significant differences were found in two factors: revenue generation and existence of potential markets. The ANOVA F-test statistic indicates significant differences that could be explained by the sustaining disruptive technologies differences seen in the earlier tests. Table VIII indicates significant differences among sustaining and disruptive technologies firms that depend on external sources of innovation in the revenue generation and market factors. Disruptive technologies firms seem to be less focused on the revenue generation or potential markets in disruptive technologies and are probably more interested in the technology itself so that they can create their own markets. Similarly differences exist between sustaining technologies firms with internal sources of innovation and disruptive technologies firms with external sources of innovation. The same logic applies here as in the earlier case. Table IX looks at the differences among four groups defined by sustaining or disruptive technologies and poor or good financial and market performance in the last three years. The four groups are: 1) firms that have poor financial performance and that are interested in sustaining technologies; 2) firms that have good financial performance and are interested in sustaining technologies; 3) firms that have poor financial performance and that are interested in disruptive technologies; and 4) firms that have good financial performance and are interested in disrup-

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TABLE VIII FACTOR HYPOTHESES TESTING

TABLE IX FACTORS ANOVA AND FACTOR MEANS AND STANDARD DEVIATIONS FOR TECHNOLOGY TYPE AND FINANCIAL PERFORMANCE

tive technologies. Significant differences exist in three of the four factors. The factors indicating product realization, revenue generation, and potential markets show significant differences among the four groups. Table X shows significant differences between sustaining technologies firms and disruptive technologies firms that have poor financial performance. The differences are in the potential market and revenue generation factors indicating that disruptive firms do not seem to attach importance to these areas in their decision to pursue these technologies. The same differences are also apparent between sustaining technologies firms with good financial performance and disruptive technologies firms with poor financial performance. These firms also show a significant difference in the product realization area. Another difference exists between disruptive technologies firms with good and poor financial performance records in the revenue generation area with good performing companies putting more importance on the revenue factor. A. Conclusions and Implications for Management Our study suggests that firms that pursue the commercialization of disruptive technologies place different importance on the product realization and on research support for the tech-

nologies than sustaining technologies firms that seem to be focused on revenue generation and market potential. The size of the firms did not seem to make much difference but this may be a problem with the firms in our sample other factors such as financial performance in the last three years seem to be a factor. Classification of firms by more than one characteristic (type of technology plus size, source of innovation, and financial performance) helped clarify some of these conclusions. The major conclusion of this paper are that: 1) Firms do utilize differing techniques to pursue disruptive technologies. 2) Firms that pursue disruptive technologies have a difficulty taking a market focused approach and must be much more creative in their approach to the market irrespective of the source of innovation, size or financial performance. 3) Sustaining technologies firms focus on existing markets and their ability to introduce new products that is traditionally their strong suit. Firms working with sustaining technologies focused on revenue generation and their cash flow potential whereas firms working with disruptive technologies seem to understand the need to develop the supporting infrastructure to realize new products. It seems that firms dealing with disruptive technology knew that they have a longer road to profitability but that it might be worth it from a risk/reward relationship. Small and large firms reacted the same way to all issues indicating that

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TABLE X FACTOR HYPOTHESES TESTING

learning has occurred in large firms requiring them to act and behave as small firms when it comes to working with technology. This might also be the Sandia effect in the sense that firms that work with Sandia anticipate major breakthroughs that will require a longer (but more profitable) path to commercialization in sustaining and disruptive technologies. The source of the innovation did not have an effect on behavior of firms but past financial performance seems to propel the groups that have done well to try to keep their advantage by working hard at getting new products to market, whereas low profitability seems to indicate that it is a result of and a cause for the inability to get things done. Differences were obvious between firms engaged in commercialization of disruptive technologies irrespective of their size and large firms focused on sustaining technologies. These differences indicate that firms interested in sustaining technologies wanted more buyers and revenue generation and depended less on government buyers and research support. Firms working on sustaining technologies wanted more distribution channels and market growth. Firms trying to commercialize disruptive technologies using external innovations were less interested in buyers and market growth. The bottom line seems to indicate that firms commercializing disruptive technologies know that markets are somewhat farther than existing products improved with sustaining technologies, but firms were willing to use external support from external research sources to further build their capabilities in disruptive technologies hoping for a major shift to their products in the near future, bringing with it new markets and new customers.

REFERENCES [1] W. J. Abernathy and K. B. Clark, “Innovation: Mapping the winds of creative destruction,” Res. Policy, vol. 14, pp. 3–22, 1985. [2] P. Anderson and M. Tushman, “Technological discontinuities and dominant designs: A cyclical model of technological change,” Administrative Sci. Quarterly, vol. 35, no. 6, pp. 604–633, 1990. [3] D. L. Birch, Job Creation in America: How Our Small Companies Put the Most People to Work. New York: Free Press, 1987. [4] J. L. Bower and C. M. Christensen, “Disruptive technologies: Catching the wave,” Harvard Business Rev., vol. 73, no. 1, pp. 43–53, 1995.

[5] P. Carroad and C. Carroad, “Strategic interfacing of R&D and marketing,” Res. Technol. Mgt., vol. 25, no. 1, pp. 28–33, Jan. 1982. [6] C. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Boston, MA: Harvard Business School Press, 1997. [7] A. C. Cooper and C. G. Smith, “How established firms respond to threatening technologies,” Acad. Mgt. Executive, vol. 6, no. 2, pp. 55–70, 1992. [8] E. Ehrenberg, “On the definition and measurement of technological discontinuities,” Technovation, vol. 15, no. 7, pp. 437–452, 1995. [9] R. Florida and M. Kenney, The Breakthrough Illusion. New York: Basic, 1990. [10] R. N. Foster, Innovation: The Attacker’s Advantage. New York: McKinsey, 1986. [11] A. Glasmeier, “Technological discontinuities and flexible production networks: The case of Switzerland and the world watch industry,” Res. Policy, vol. 20, no. 5, pp. 469–485, 1991. [12] D. S. Isenberg, “The mother of all disruptions,” America’s Network, vol. 103, no. 11, p. 12, 1999. [13] S. M. Kaplan, “Discontinuous innovation and the growth paradox,” Strategy Leadership, vol. 27, no. 2, pp. 16–21, 1999. [14] S. K. Kassicieh and R. Radosevich, “The participant roles in publicsector technology commercialization,” in From Lab to Market: Commercialization of Public-Sector Technology, S. K. Kassicieh and H. R. Radosevich, Eds. New York: Plenum, 1994, pp. 125–135. , “Mechanisms and processes of technology transfer and com[15] mercialization,” in From Lab to Market: Commercialization of Public-Sector Technology, S. K. Kassicieh and H. R. Radosevich, Eds. New York: Plenum, 1994, pp. 197–208. [16] B. A. Kirchhoff, Entrepreneurship and Dynamic Capitalism. Greenfield, CT: Praeger, 1994. [17] B. Kirchhoff and S. Walsh, “Entrepreneurship’s role in commercialization of disruptive technologies,” in Unternehmer und Unternehmensperspektive fur Klien-und Mittelunternehmen Berlin, Germany, 2000, pp. 323–332. [18] C. Lambe and R. E. Spekman, “Alliances, external technology acquisition, and discontinuous technological change,” J. Product Innovation Mgt., vol. 14, no. 2, pp. 102–116, 1997. [19] J. Linton, “An improved method and forecast for the world-wide market growth of MEMS,” in The International MEMS, Microsystems, and Top Down Nano Technology Roadmap, Walsh and Elders, Eds. Naples, FL: MANCEF, The Micro and Nano Technology Commercialization Education Foundation, 2002, pp. 158–173. [20] G. Lynn, J. Morone, and A. Paulson, “Marketing and discontinuous innovation: The probe and learn process,” California Mgt. Rev., vol. 38, no. 3, pp. 8–37, 1996. [21] E. Mansfield, The Economics of Technological Change. New York, New York: W.W. Norton, 1968. [22] D. Mckee, “An organizational learning approach to product innovation,” J. Product Innovation Mgt., vol. 9, no. 3, pp. 232–245, 1992. [23] P. Meyers and F. Tucker, “Defining roles for logistics during routine and radical technological innovation,” J. Acad. Marketing Sci., vol. 17, no. 1, pp. 73–82, 1989.

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[24] G. Moore, Crossing the Chasm. New York: Harper Business, 1991. [25] J. Morone, Winning in High Tech Markets. Boston, MA: Harvard Business School Press, 1993. [26] J. Neter, W. Wasserman, and M. Kutner, Applied Linear Statistical Models. Homewood, IL: Irwin, 1990. [27] J. C. Nunally, Psychometric Theory. New York: McGraw-Hill, 1978. [28] C. K. Prahalad and G. Hamel, Competing for the Future. Boston, MA: Harvard Business School Press, 1994. [29] M. Porter, Competitive Advantage; Creating and Sustaining Superior Performance. New York: The Free Press, 1985. [30] M. P. Rice, G. C. O’Connor, L. S. Peters, and J. G. Morone, “Managing discontinuous innovations,” Res. Technol. Mgt., vol. 41, no. 3, pp. 52–58, 1998. [31] R. Radosevich and S. Kassicieh, “Strategic challenges to competitiveness through public-sector technology,” California Mgt. Rev., vol. 35, no. 4, pp. 33–50, 1993. [32] P. D. Reynolds, “New firms: Societal contribution versus survival potential,” J. Business Venturing, vol. 2, pp. 231–246, 1987. [33] J. A. Schumpeter, The Theory of Economic Development. Cambridge, MA: Harvard Univ. Press, 1934. [34] M. L. Tushman, P. C. Anderson, and C. O’Reilly, “Technology cycles, innovation streams, ambidextrous organizations: Organizational renewal through innovation streams and strategic change,” in Managing Strategic Innovation and Change, Tushman and Anderson, Eds. New York: Oxford Univ. Press, 1997. [35] M. L. Tushman and R. Lori, “Organizational determinants of technological change: Toward a sociology of technological evolution,” Res. Organizational Behavior, vol. 14, pp. 311–347, 1992. [36] A. Usher, A History of Mechanical Inventions. Cambridge, Mass.: Harvard Univ. Press, 1954. [37] R. Veryzer, “Discontinuous innovation and the new product development process,” J. Product Innovation Mgt., vol. 15, no. 4, pp. 304–321, 1998. [38] E. Von Hipple, “Economics of product development by users: The impact of sticky local information,” Mgt. Sci., vol. 44, no. 5, pp. 629–643, May 1998. [39] S. Walsh, Commercialization of MicroSystems – Too Fast or Too Slow: SPIE, Int. Soc. Opt. Eng., 1996, pp. 12–26. [40] S. Walsh and J. Elders, “Introduction to disruptive technology roadmap development,” in Int. MEMS, Microsystems, and Top Down Nano Technology Roadmap, Walsh and Elders, Eds. Naples, FL: MANCEF, The Micro and Nano Technology Commercialization Education Foundation, 2002, pp. 26–32. [41] S. Walsh and J. Linton, “Infrastructure for emerging markets based on discontinuous innovations: Implications for strategy and policy makers,” Eng. Mgt. J., vol. 12, no. 2, pp. 23–31, 2000.

Suleiman K. Kassicieh (M’88) is the Regents’ Professor of Management of Technology and Albert Franklin Black Professor of Entrepreneurship, and Chairman of the Department of Finance, International and Technology Management at the Anderson School of Management at the University of New Mexico. He has consulted with a number of national and international organizations such as Los Alamos and Sandia National Laboratories in a number of areas such as strategic planning, information technology, and technology commercialization. He has also consulted on business development with a large number of high-tech startups. He teaches in the areas of technology commercialization, technology assessment, and equity/venture capital. He has over 100 published technical and management papers and is author of the book From Lab to Market: Commercialization of Public Sector Technologies (New York: Plenum, 1994).

Steven T. Walsh (S’94–M’95) received the B.S. degree in biomedical engineering and the Ph.D. degree in strategy with specialization in management of technology and entrepreneurship from Rensselaer Polytechnic Institute, Troy, NY. He also holds a certificate of Advanced Studies in business administration from Northeastern University and an MBA in marketing and new product planning. Dr. Walsh is the Director of Technological Entrepreneurship at the University of New Mexico where he has been awarded the Black Professorship of Entrepreneurship. He has been a director of a Fortune 500 company division and president of entrepreneurial firms. He has published well over 100 published articles serving both the academic and practitioner communities. He has been a plenary or invited speaker numerous at many universities and national laboratories in the United States and on four other continents. Further, he has served as a plenary speaker for many academic and industrial organizations such as the International Association of Management of Technology (IAMOT), SPIE (The International Society for Optical Engineering), MANCEF (the Micro and Nano technological Commercialization Education Foundation), SEMI (Semiconductor Equipment and Materials International), and IAPD (International Association of Product Development Professionals). He is the Founding President for the MANCEF. Dr. Walsh is a member of the board of reviewers for the IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, an Associate Editor for Microsystems Commercialization and Silicon processing for the SPIE Journal of Microlithography, Microfabrication, and Microsystems, an Area Editor for the Engineering Management Journal, and a Special Issue Editor for IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT and other journals. He is Co-chair for the international technology roadmap for Micro and Top Down Nano Systems, a Board Member of the MESA Institute at Sandia National Laboratories, and a Member of the Board of advisors of R&D magazine’s Micro Machine Devices magazine.

John C. Cummings received the B.S., M.S. and Ph.D. (1973) degrees from California Institute of Technology, Pasadena. His Ph.D. research involved the development of a cryogenic shock tube and the study of strong shock waves in gaseous and liquid helium. He is currently on temporary assignment as a Technical Advisor to the White House Homeland Security Transition Planning Office (planning for the new Department of Homeland Security). Before his current position, he was the Deputy to the Chief Technology Officer and Manager of the Science and Technology Strategic Management Unit Office at Sandia National Laboratories in Albuquerque, NM. He has worked at Sandia for 26 years serving in a wide variety of technical staff and management positions. His technical work includes research in experimental fluid mechanics, combustion, and the use of laser-based instrumentation. Before joining Sandia, he was employed by the Engineering Sciences Department at TRW Systems, Inc., where he conducted studies of HF and DF chemical lasers. He is the author or coauthor of over 50 technical publications and reports. Dr. Cummings is a member of the American Physical Society Division of Fluid Dynamics, and he served as the U.S. representative to the International Atomic Energy Agency working on the mitigation of hydrogen combustion hazards in nuclear power plants.

Paul J. McWhorter is one of the pioneering researchers in the field of microelectro mechanical systems (MEMS). In 1992, he initiated Sandia’s MEMS Program and grew the program to one of the largest in the country. In October of 2000, he left Sandia to form MEMX, a start-up company focused on revolutionary telecommunications products based on MEMS and he is presently serving as CTO. Dr. McWhorter’s work has been recognized with five IEEE best paper awards, two R&D 100 awards, Industry Week’s “Top Technology of the Year” Award, and Science News’ Top Development of the Year Award. He was named 1998 New Mexico Inventor of the year and Sandia’s Outstanding Corporate Inventor. He has been featured on the ABC evening news with Peter Jennings, CNN, and in publications including Forbes, Fortune, and Business Week.

KASSICIEH et al.: FACTORS DIFFERENTIATING THE COMMERCIALIZATION

Alton D. Romig received the B.S., M.S. and Ph.D. degrees in materials science and engineering from Lehigh University in 1975, 1977, and 1979, respectively. In 1979, he joined Sandia National Laboratories as a member of the technical staff, Physical Metallurgy Division. After a variety of management assignments, he was named Director, Materials and Process Sciences in 1992. In 1995, he was named Director, Microelectronics and Photonics, and in 1998 Director of Microsystems Science, Technology and Components. He served in this capacity until attaining his present position in 1999. He is currently Vice President, Science and Technology and Partnerships and Chief Technology Officer at Sandia National Laboratories, Albuquerque N.M. He is Chief Scientific Officer for the Nuclear Weapons program. He is also accountable for Sandia’s interactions with industry and the Laboratories’ Campus Executive program. In addition, he is responsible for the Laboratory Directed Research & Development program (DOE’s IR&D). He has approximately 160 technical publications, is the co-author of three textbooks, and holds two patents. He also serves on the Boards of Technology Ventures Corporation, a Lockheed Martin subsidiary dedicated to technology commercialization, and the National Coalition for Advanced Manufacturing (NACFAM). Dr. Romig has received several awards, including the Burton Medal (1988), awarded by the Electron Microscopy Society of America to an Outstanding Young Scientist; the K.F.J. Heinrich Award (1991), given by the Microbeam Analysis Society to an Outstanding Young Scientist; the ASM Silver Medal for Outstanding Materials Research (1992); and the Acta Metallurgica International Lectureship (1993–1994). He is a Past-President of ASM, International (formerly American Society for Metals). He is currently the Chair of the ASM Educational Foundation. Other current professional activities include serving on, and chairing, a number of committees for ASM International, The Minerals, Metals and Materials Society, the Materials Research Society and the Microbeam Analysis Society (MAS). He is active on a number of National Academy of Engineering/National Research Council Committees and Boards.

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W. David Williams received the A.B. degree from University of California, Irvine, in 1972, and the Ph.D. degree in physics from Cornell University, in 1976. He heads the first satellite office of Ardesta, located in Albuquerque, NM, which opened in August 2001. He serves as Vice President and CEO of Ardesta’s Southwest Office. Before joining Ardesta, he was the Director of Microsystems Science, Technology and Components Center at Sandia National Laboratories. While there, he directed the research, development and engineering of microelectronic, photonic, and microelectromechanical devices and systems. He was responsible for the operation of two fabrication facilities.