Innovation strategy and financial performance

Description
The report about innovation strategy and financial performance covers topics like leadership orientation , its level of emphasis on process and product innovation, its use of internal and external sources of innovations, and its intensity of investment in innovation.

PRODUCTION

AND OPERATIONS MANAGEMENT Vol. 2, No. I, Winter 1993 Prinred in U.S.A.

INNOVATION STRATEGY AND FINANCIAL PERFORMANCE IN MANUFACTURING COMPANIES: AN EMPIRICAL STUDY *
SHAKER A. ZAHRA
AND

SIDHARTHA

R. DAS

Department of Management, College of Business Administration, Georgia State University, Atlanta, Georgia 30303, USA Department of Decision Sciencesand MIS, School of Business Administration, GeorgeMason University, Fairfax, Virginia 22030, USA
An innovation strategy for the manufacturing function covers four areas: a firm’s desired innovation leadership orientation (i.e., being a leader versus being a follower), its level of emphasis on process and product innovation, its use of internal and external sources of innovations, and its intensity of investment in innovation. We examine two models of the association between manufacturing companies’ innovation strategy and their financial performance. The first examines the variations in company financial performance as a function of the simultaneous effect of the dimensions of innovation strategy. The second is a sequential model that suggests a causal sequence among the dimensions of innovation strategy that may lead to higher performance. We used data from a sample of 149 manufacturing companies to test the models. The results ( 1) support the importance of innovation strategy as a determinant of company financial performance, (2) suggest that both models are appropriate for examining the associations between the dimensions of innovation strategy and company performance, and (3) show that the sequential model provides additional insights into the indirect contribution of the individual dimensions of innovation strategy to company performance. Finally, we discuss the implications of these results for managers. (MANUFACTURING INNOVATION; INNOVATION STRATEGY; COMPANY PERFORMANCE)

1. Introduction Concern over the global competitiveness and productivity of American manufacturers has drawn attention to the importance of a company’s manufacturing innovation activities to its financial performance (Thurow 1992). Manufacturing innovation includes creating, refining, and extending products, processes,and technologies. Such innovations can improve the global standing of US manufacturing companies and help them regain their status as world-class producers. By using new technology, creating and commercializing or marketing new products, and adopting innovative manufacturing processes,American companies’ can effectively solve their competitive problems ( Swamidass 1986 ) .
* Received August 1992; revision received June 1993; accepted September 1993. 15 1059-1478/93/0201/000$1.25
Copyright Q 1993, Production and Operations Management Society

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To innovate its manufacturing processes, a company must develop a formal and comprehensive innovation strategy ( Manu 1992; West 1992). (In this paper we use the term innovation strategy to refer to innovations within the manufacturing function.) This strategy defines the manufacturer’s objectives in pursuing innovation by delineating both the ends (what to innovate) and the means (how to achieve it). Integrating the diverse activities that lead to the creation, development, and commercialization of products and techhologies enables the company to maximize its payoff from innovation efforts. A manufacturing innovation strategy can guide executives’ actions in four ways. First, it establishes innovations in products and processes as a competitive priority (Ettlie and Reza 1992; Leong, Snyder, and Ward 1990)) thus linking these activities to the firm’s competitive strategy (i.e., the long-term plan the company follows in pursuing its competitive goals). This linkage helps to reduce the uncertainties associated with the innovation process, a process that has been described as managed chaos and a process that is riddled with ambiguities and has uncertain outcomes (Quinn 1986). These uncertainties surround both the creation of products (Gupta and Wilemon 1990) and the adoption of process innovations, e.g., new machinery and computer-integrated manufacturing systems (Gerwin and Tarondeau 1982). Having a clear direction regarding the appropriate mix of product and process innovations, a firm can reduce conflicts about goals and tactics and also promote employee commitment to innovation. Further, executives can use innovation strategy to reduce uncertainty by selecting appropriate projects that can mesh well with the company’s goals, to marshal1 support for these projects, and to focus employee attention on their company’s long-term needs for novel products and technologies (McLimore and Larwood 1988). Second, a manufacturing innovation strategy guides executives in allocating scarce resources by favoring projects that enhance the company’s manufacturing competence and skills. Consequently, these innovations help to distinguish the company’s products and goods in the marketplace, give the company leverage in negotiations with suppliers, and aid in preempting competitors’ moves to attract customers away from the company. Third, this strategy forces executives to delineate the focus and source of future manufacturing innovations; considering the company’s strategy (Burgelman and Sayles 1986); industry conditions (Grossi 1990), and internal skills, resources, strengths, and weaknesses (Rosenthal 1984). This helps them to ensure that their innovation efforts match the demands of competitive success. Finally, a manufacturing innovation strategy also helps the firm to sharpen its competitive advantage by differentiating its products and creating value to customers (Porter 1985 ). When the new product or process is different from existing ones, the firm’s advantage is protected from imitation by competitors. A firm can use innovative products to protect its existing markets or to target new niches, thereby achieving superior financial performance over its rivals (Butler 1988; West 1992). Researchers have not comprehensively examined the links between a company’s formal manufacturing innovation strategy and its financial performance. Although some have tried to examine the association between some aspects of innovation strategy (e.g., product innovation) and company performance, no one has published a study that models the collective effects of the dimensions of innovation strategy on company financial performance. This combined effect on company performance

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often results from synergy among innovation activities. Finally, the literature is unclear on the appropriate approach to modeling the collective effect of innovation strategy on company performance. Past researchers have employed multiple regression as the primary analytical tool (e.g., Hambrick, MacMillan, and Barbosa 1983; Hambrick and MacMillan 1985); in doing so they often ignore the potential logical order among the dimensions of innovation strategy. Thus, rather than “assuming” a simultaneous effect of innovation strategy on performance, researchers should explore other types of relationships, such as sequential relationships that are typically embodied in path analysis and similar techniques. In this paper, we empirically examine the association between a company’s manufacturing innovation strategy and its financial performance. We first present the major dimensions of innovation strategy. Next, we introduce two models of the potential association between innovation strategy variables and company financial performance. The first model examines variations in company financial performance as a function of the simultaneous effect of the dimensions of innovation strategy. We test this model using multiple regression analysis. We test the second model, which suggeststhat a “causal sequence” among the dimensions of innovation strategy may lead to superior company performance, using path analysis. Finally, we compare the results from the two models and discuss their implications for managerial decision making. Overall, we aim to contribute to the literature in three ways: ( 1) to present a comprehensive definition of innovation strategy, thus setting the stage for improved scholarly exchange on the topic; (2) to show that innovation strategy makes a significant difference in company performance; and (3) to introduce two models that explore the association between innovation strategy and company performance that executives can use to establish an effective innovation strategy. 2. Dimensions of Innovation Strategy An innovation strategy is a multidimensional concept that embodies four dimensions ( Porter 1985; Kamm 1987; Pearson 1990; Ambrosio 199 1; Thurow 1992; West 1992 ): an orientation of the firm toward innovation leadership (Maidique and Patch 1988), types of innovation (Betz 1987)) sources of innovation (Mansfield 1988)) and level of investment in innovation (Thompson and Ewer 1989).

Leadership Orientation
This dimension indicates whether a firm follows a first-to-the-market, second-tothe-market, or late-entrant, imitator posture in its innovation activities (Porter 1985 ) . In a manufacturing context, a company that adopts a first-to-the-market posture is usually on the cutting edge of product and process innovations, using the novelty and uniqueness of its products to gain a competitive edge. Although the first-to-themarket orientation is sometimes equated with entrepreneurs and their high technology ventures (Khan and Manopichetwattana 1989)) well-established firms (e.g., Apple, Merck, Microsoft, and 3M) also pursue such a strategy (West 1992). A company that follows a second-to-the-market orientation usually monitors innovations introduced by its leading rivals and quickly copies these innovations. This orientation stressesspeed in imitating its rivals’ brands and models (Maidique and Patch 1988). A commitment to adding value to the customer through improvements or modifications to its rivals’ brands or models typifies this orientation. The company

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does not undertake leading-edge research but instead focuses on improving on its rivals’ products. Compaq, Emerson Electronics, and Zenith Computers are wellknown firms that follow this orientation. A late-entrant, imitator orientation signifies a firm’s commitment to copying its competitors’ successful brands, products, or models and offering inexpensive substitutes to them. A late entrant usually adds functions to the product, emphasizes ease of use, and competes based on low cost. Dell Computers and Leading Edge follow this orientation. Hayes and Abernathy ( 1980) discuss the potential trade-offs associated with imitating versus developing new products.

Types of Innovation
This dimension refers to the combination (portfolio) of manufacturing innovations (product and process) a firm pursues or generates over time. In this study, we have not considered innovations in other related business applications, such as information technology and innovative organizational designs. Instead, we focus on product and process innovation-a focus that is consistent with the results of a survey of manufacturing managers that concluded that both process and product innovations are important to a company’s business strategy (Schroeder, Anderson, and Cleveland 1986). Further, an extensive review of the literature by Anderson, Cleveland, and Schroeder ( 1989) shows that within manufacturing managerial choices usually center on product and process technologies. Product innovation results in the creation and introduction of radically novel products or modifications in existing ones (Krubasik 1988; Pale 1988). Research shows that product innovation can be risky. For example, Gupta and Wilemon ( 1990) suggest that poor definition of product requirements, technological uncertainty, lack of senior management support, lack of resources, and poor project management can handicap product development efforts. By overcoming these problems, companies can reduce the risks associated with new products and, in fact, create a sustainable competitive advantage in their marketplace. Indeed, a recent analysis of 1,48 1 new product announcements by 263 companies between 1975 and 1988 has concluded that product innovations have increased the market value of innovating companies by more than $10 billion (Chaney and Devinney 1992; Devinney 1992 ). Skinner ( 1984, p. 116) proposes that “innovation in operations equipment and process technologies can be used strategically as a powerful competitive weapon.” Process innovations lead to new methods of operation by producing new manufacturing technologies or improving existing ones (Leonard-Barton 199 1) . They can also help companies to achieve economies of scale or scope that can be used to lower costs and prices. Indeed, the future global success of US manufacturers depends on their proficiency in process innovation (Thurow 1992). Recently, process innovations have become more important than product innovations in determining global success. Although US companies have excelled in developing new products, successful Japanese and German manufacturers have stressed process innovations in their bids for world leadership. Thus, US companies’ continuing focus on product innovation may be out of step with the growing global emphasis on process innovation. This gap has been highlighted by the results of a recent study of US companies’ research and development (R&D) spending between 1979 and 1985 (Caravatti 1992). It concluded that although US companies devoted only 19 percent of their R&D expenditures to process innovations, Japanese companies devoted nearly 62 percent to this purpose.

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A formal innovation strategy allows the firm to simultaneously consider product and process innovations. This is important because process innovations are sometimes tied to product innovations, because often a new product cannot be manufactured without breakthroughs in process (Thurow 1992). Consequently, Finkin ( 1983) suggested that product development and manufacturing process development function best when they are integrated. Also, as industries and markets mature, innovation efforts tend to shift from creating products to cost-reducing process innovations (Khan and Manopichetwattana 1989). Firms may vary a great deal in the combination of product and process innovations they emphasize (Porter 1985 ) . Therefore, it is important to examine the association between the firm’s innovation leadership orientation and its innovation portfolio. We try to clarify whether leaders, followers, and imitators pursue different combinations of product and process innovations.

Sources
This dimension specifies the locus of innovation activities in a firm: internal or external or both (Betz 1987; Mansfield 1988). With internal sources of innovation, a firm relies on its own in-house R&D efforts to generate product or process innovations. Kodak, Motorola, and 3M have relied heavily on their internal R&D activities in creating new products and processes. IBM and Microsoft also follow this strategy. If a company relies on external sources, it will acquire innovations through purchase, licensing agreements, acquisition of other firms, or joint ventures with suppliers, customers, or other firms (Dosi 1988; Ettlie 1988; Manahan 1989; Gupta and Wilemon 1990; Hill 1992). Research shows that companies emphasize different sources of innovation. For instance, a study of new-venture firms in the computer and communications equipment industry (McDougall, Deane, and D’Souza 1992) showed that corporate-sponsored ventures emphasize patented technology and product development. In contrast, new ventures sponsored by independent entrepreneurs use external sources, such as public domain technology, and do not emphasize product development. Gold ( 1987) suggeststhat companies use both internal and external sources to accelerate process and product innovations. IBM has made extensive use of both internal R&D and external sources of innovation in its attempt to control the personal computer market.

Investment
This dimension embodies the financial, technological, and human capital investments associated with manufacturing innovation activities (Thompson and Ewer 1989; Leong, Snyder, and Ward 1990). Financial investments include spending on R&D projects and purchasing innovations developed elsewhere. Technological investments are expenditures on infrastructure equipment and basic facilities required for innovation (Thurow 1992). Human capital investments include salaries, training, and other costs associated with developing staff (Kamm 1987). Theoretically, there are many different potential links between the four innovation strategy dimensions, and it is important to focus on the fit between the dimensions. One must effectively match (seek consistency) one’s choices among the innovation strategy dimensions. Choices in these dimensions should be compatible, thus reinforcing and supporting one another (Venkatraman 1989). Fit reduces the misuse of resources and enables a firm to attain high performance levels.

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3. Modeling Innovation Strategy and Company Performance Links How can the associations between the dimensions of a company’s innovation strategy and financial performance be modeled? The literature suggeststwo possible approaches (Ettlie 1983; Ettlie, Bridges, and O’Keefe 1984; Kamm 1987). In the first, innovation strategy dimensions are assumed to influence company performance directly and simultaneously. The second approach suggestsa logical sequence among innovation strategy variables. Hence, the associations between certain innovation strategy dimensions and company performance may be indirect; that is, the effect of one dimension may be moderated by the influence of another dimension.

Simultaneous Model
This model posits that careful planning of the four dimensions of innovation strategy will lead to superior company financial performance. It suggeststhat different dimensions of innovation strategy will influence company performance simultaneously (Kamm 1987; Teece 1988), as depicted in Figure 1. These dimensions will vary in their associations with company performance. The simultaneous model builds on the potential synergy among the dimensions of innovation strategy, suggesting that the total effect of innovation strategy on company performance will exceed the sum of the contributions of its individual dimensions. This synergy has two major sources: savings, because of the clear priorities embodied in developing an innovation strategy, and the mutual support among the dimensions. We tested the model using multiple regression to consider the combined effects of the four dimensions (the “independent” variables) on company financial performance (the “dependent” variable). Researchers have employed the simultaneous model in several studies examining the association between a firm’s innovation strategy and its financial performance (e.g., Hambrick, MacMillan, and Barbosa 1983; Hambrick and MacMillan 1985 ) .

Leadership

I

Comwy
Financial Petfomwwe

FIGURE 1. A Simultaneous Model of Innovation Strategy-Company Financial Performance Links.

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They recognized the strengths of the simultaneous model, which include ( 1) a clear delineation of the direct association between an innovation strategy variable and financial performance; (2) the ability to examine the unique contribution of particular variables (e.g., R&D investment) to company performance, once other variables have been considered; and ( 3 ) the opportunity to integrate diverse sets of variables (e.g., environment and strategy) as they determine the components of innovation strategy and their effects on company performance. Although the studies employing the simultaneous model have enriched our understanding of the interplay between innovation strategy and company performance, they have two shortcomings. First, they ignore the potential indirect effect of a variable (e.g., innovation leadership posture) on performance through its impact on another variable (e.g., type of innovation used). By considering indirect effects, one can develop an accurate estimate of returns for innovations. Second, past studies have overlooked the logical sequence of relationships among variables. For example, investment in R&D per se may not have a profound effect on company performance (Thurow 1992). Only when this investment is deployed strategically among new products or processes is the effect on company performance positive. These two shortcomings can be overcome by using a sequential model. Sequential Model This approach posits that a logical sequence may exist among the four innovation strategy dimensions (Porter 1985), reflecting an ordered set of relationships among them. Certain choices (e.g., leadership posture) must precede others (e.g., level of investment ) . The sequential model also acknowledges the potential indirect influence of some innovation strategy dimensions on company performance (Asher 1983). Even though a variable may not influence performance directly, as assumed in the simultaneous model, it may still influence other important dimensions that, in turn, affect company performance. This occurs because innovation strategy dimensions may depend on one another, as depicted in Figure 2.

FIGURE 2. A Sequential Model of Innovation Strategy-Company

Financial Performance Links.

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A. ZAHRA

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R. DAS

Figure 2 shows the sequential model and the hypothesized order of relationships among the dimensions of innovation strategy. The rationale for sequencing the variables in the order shown is based on theory. Still, because other sequences may be posited by other researchers, further empirical research is necessary to test alternative models. The logical starting point in Figure 2 is the company’s choice of its intended innovation leadership position. The firm makes this choice based on its chosen external environment, its competitive strategy, its strengths and weaknesses, and the availability of resources (Porter 1985 ) . Once they choose an innovation leadership orientation, executives then address two issues. The first is, what types of innovation will the firm emphasize? For the manufacturing function, they should select a portfolio of product and process innovations. They will need to consider the firm’s competitive strategy, market definition, and customer profile. They can then clearly articulate the extent of the company’s emphasis on process and product innovations. Next, executives must address a second question: Which sources should the company use in developing or securing manufacturing innovations? They will base their selection of innovation sources on the company’s planned leadership position. If the company pursues a first-to-the-market orientation, it will rely heavily on internal sources in generating its process and product ideas (Porter 1980, 1985 ) . A company that follows a second-to-the-market orientation will use both internal and external sources ( Burgelman and Sayles 1986 ) . A late-entrant, imitator firm will use external sources extensively in developing its product and processes and then rely on its internal facilities to improve on these innovations. The executives’ choices of the types (process and product) and sources (internal and external) of innovation determine the levels of investments. Leadership orientation will also influence the level of company investment in innovation. A first-tothe-market orientation requires significant investments in both theoretical and applied research, employment of highly skilled researchers and staff, development of information systems that can scan the environment to identify important opportunities, and maintenance of state-of-the-art research facilities. Firm’s adopting a second-to-the-market or late-entrant orientation face quite different situations. Companies that adopt either of these orientations will require different skills and resources that may not call for such high levels of investment. Corporate investment in manufacturing innovation is expected to have a positive direct effect on company performance, and past empirical research that shows higher corporate spending on R&D is associated with higher company performance (Dosi 1988; Thompson and Ewer 1989; Van den Kroonenberg 1989). Leadership orientation also has a direct influence on corporate financial performance. Growing evidence shows that pioneers (first movers) improve their financial positions if they implement their innovation strategies effectively (Porter 1985; Butler 1988). Researchers have employed a path analytic framework in past studies examining sequential associations between innovation strategy and company performance (Ettlie 1983; Ettlie, Bridges, and O’Keefe 1984). Path analysis enables researchersto examine the effects of selected variables on other variables of interest. It helps them to identify direct and indirect effects in a complex system of variables, and allows them to include intervening variables in the analysis easily (Swamidass and Newell 1987).

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In adopting the path analytic approach, we have adhered to recommended methodology by including only those variables or relationships that have some theoretical or logical support (Asher 1983) and keeping the number of variables in the model to a minimum (Young 1977). 4. Method Sample We mailed a questionnaire to the presidents (or highest ranking executives) of manufacturing firms throughout the United States. These firms covered six fourdigit Standard Industrial Classification (SIC) consumer and industrial goods groups. To qualify for inclusion, a company had to generate at least 70 percent of its revenue from a given industry, thus corresponding to the single or dominant business definition (Dess 1987 ). A total of 5 13 manufacturing companies met this criterion. We used two mailings, 1 month apart, and received 149 complete responses (36 additional surveys are undeliverable), for a response rate of 3 1.9 percent. Each response represented a single company; no two responses were from the same firm. Responding firms averaged $689.6 million annual sales, with a range from $200 to $2,286 million. Industries included canned fruits and vegetables, dehydrated fruits and vegetables, biological products, fabricated metal products, food product machinery, and apparel. These industries, which differed in their stage of evolution and competitive intensity, provided an interesting setting in which to examine the association between innovation strategy and company performance. We compared responding and nonresponding firms in sales, size, number of employees, and SIC, using multivariate analysis of variances. We found no significant differences between these two groups, indicating that the sample did not differ significantly from its population. Measures We measured the dimensions of innovation strategy using indices developed from executives’ responses to multiple items. We selected items corresponding to each index based on theory. In addition, we ran a principal component analysis to determine if the 28 innovation items fell into their respective theoretic dimensions. The results supported the separation of the 28 items into the six dimensions shown in the Appendix. We formed innovation strategy indices by summing raw innovation item scores; we then divided the total by the relevant number of items to produce an average score. (The results reported in the paper did not change significantly using this procedure from those found when we used factor scores derived from principal component analysis.) The Appendix shows the measures and items. Measuring innovation is problematic (Bigoness and Perreault 198 1) . Therefore, in developing the measures, we followed three criteria to enhance the reliability of the scales. ( 1) Throughout the survey we used the term company to avoid the confusion that arises from using related concepts such as unit or division. We asked the respondents to consider only their immediate company in completing the survey. (2) Each measure consisted of multiple items, thereby capturing as much of the theoretic domain of the constructs as possible. We developed the items based on the definitions outlined earlier in the paper and derived from the literature. (3) To further ensure accuracy, we asked the executives to compare their companies to the industry

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and to their competition. Because innovation strategy is a comparative term (Hambrick, MacMillan, and Barbosa 1983; Buzzell and Gale 1987), the efficacy of a particular dimension depends on how well the firm emphasizes the variable compared with its rivals and industry. Consequently, the current measures reflected the extent to which a company emphasized a particular variable as well as the company’s relative emphasis compared with its industry and with its competition. We developed the innovation strategy indices (Xl through X6) so that a high score would indicate greater reliance on or use of a dimension and vice versa. 1. LEADERSHIP ORIENTATION (Xl ) . We used an index consisting of six items to gauge manufacturing innovation leadership. A high score on the index showed a high disposition toward pioneering product and process innovation. A low score indicated a strong disposition to use the follower or imitator approach. The scale items were consistent with the definition of innovation leadership, as suggested by Foster ( 1986)) Kimura ( 1990)) and Robinson ( 1990). Collectively, these authors suggest that innovation leaders are first to develop and introduce new products to their markets. 2. PROCESS INNOVATION (X2). We measured this dimension using a five-item index consisting of responses to four items derived from past research (Kim 1980; Bigoness and Perreault 1981; Ettlie 1983) . Research suggeststhat measures of process innovation should consider the firm’s investments in, and adoption of, new production methods and technologies ( Buzzell and Gale 1987 ) . 3. PRODUCT INNOVATION (X3 ) . We measured this dimension using a five-item index based on the literature (Ghoshal and Bartlett 1988; Birley and Westhead 1990; Covin and Prescott 1990). It recommends considering the intensity (level) of product innovation and the firm’s emphasis on modifying existing products, both in absolute terms and in comparison with the competition. 4. EXTERNAL INNOVATION SOURCE (X4). We measured this dimension using a four-item index developed following past research. Von Hippel ( 1988) suggests that external sources include suppliers, customers, and other companies. Kamm ( 1987) also suggeststhat acquisitions and licensing are important innovation sources. Likewise, Hill ( 1992) considers licensing a major external source of innovation. We also used a four-item index to 5. INTERNAL INNOVATION SOURCE (X5). measure this dimension. Following the literature (Von Hippel 1988; Pennings and Harianto 1992), these items gauged a company’s emphasis on its R&D facilities in developing and introducing new products and proprietary technologies (Thurow 1992) and commitment to maintaining a highly skilled R&D unit (Porter 1985 ) . 6. INVESTMENT (X6). We used a five-item index to measure this dimension. These items reflected the company’s resource commitment to R&D and innovative ventures (Frank0 1989). Moreover, they stressed the firm’s financial commitment to R&D as compared with its rivals (Hambrick, MacMillan, and Barbosa 1983) or to the industry average (Hitt, Hoskisson, and Ireland 1990). Because there are wide interindustry variations in R&D investments (Hoskisson and Johnson 1992), this scale helps to avoid a shortcoming of past research, namely the use of absolute measures of R&D. 7. COMPANY PERFORMANCE (X7). We used three financial criteria to measure company financial performance: net profit margin, growth in sales, and return on

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assets.We defined each as the average of the most recent 3-year period. In addition to their wide use and acceptance in strategic management research (Hofer 1983), these criteria had specific advantages within the context of this study. Growth in sales reflected how well a company related to its external environment through innovation-a major source of profits and sales ( Schendel and Hofer 1979). Net profit margin provided an indication of a firm’s ability to improve its margin as a result of differentiated products, new production processes, or novel innovation. Finally, return on assets showed a company’s ability to use innovations to make its assets productive. The appendix contains exact definitions and response format used in the questionnaire. Briefly, we calculated the measures as follows: net profit margin = net income after interest and taxes/net sales; growth in sales = percent change in a company’s net sales over the past 3 years; return on assets( ROA) = net income after interest and taxes/total assets. Executives provided data on company performance. Researchers into strategic management have commonly relied on executives for data on company performance (e.g., Daft, Sormunen, and Parks 1988; Ramanujam and Venkatraman 1987). Data on some companies, especially strategic business units (SBUS) of corporations, were not easily accessible in secondary sources. For instance, COMPUSTAT had data on only 45 of the 149 SBUS in the current sample. In addition, some companies were privately held, which made it difficult to collect data on their performance. To ensure the reliability of data on financial performance, we defined each criterion in the survey instrument to minimize misinterpretations; we took the definitions from Gibson and Boyer ( 1979). In addition, we used data from COMPUSTAT and corporate documents (such as 10-K reports) to validate the accuracy of survey responses. Data on a subset of 45 firms were available from secondary sources. We then correlated the survey-based performance figures with data from COMPUSTAT. The average correlation between data from the two sources on the three performance criteria was 0.72 ( p < 0.0 1)) supporting the reliability of the survey performance measures. Thereafter, we used performance data for the 149 companies in subsequent analyses. Our comparison showed that we had collected reliable, objective data from executives on their companies’ performance. Having established the reliability of the performance data, we next focused on examining the simple correlations among these measures. Correlations averaged 0.83 (p < 0.00 1) . Therefore, we subjected the measures to a factor analysis with varimax rotation, yielding one significant factor (eigenvalue = 1.3 1) . To reduce redundancy in the measures and alleviate problems resulting from multicolinearity, we developed a “company financial performance factor” (CFPF) and used it in subsequent analyses. We developed the CFPF by multiplying the raw item scores on the survey by their corresponding factor loadings. The sum of this process represented the value of a company’s CFPF. 5. Analysis and Results Table 1 presents the means, standard deviations, and intercorrelations among the dimensions of innovation strategy. Cronbach coefficient alpha (01) for the innovation strategy measures are shown at the diagonal of Table 1. Because all measures have (YS 0.80 or above, we concluded that they were reliable. of

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TABLE 1 Means, Standard Deviations, and Intercorrelations Among Dimensions of Innovation Strategy Dimensions X1 -Leadership X2-Process innovation X3-Product innovation X4-External source X5-Internal source X6-Investment level Xl 0.84 0.22 0.28 -0.21 0.38 0.36 x2 0.85 0.28 -0.24 0.22 0.27 x3 x4 x5 X6 d 18.7 15.2 18.0 12.6 12.9 13.0 SD 5.5 3.7 6.5 6.3 5.2 8.5

0.84 0.24 0.30 0.34

0.81 0.22 0.27

0.82 0.42

0.85

Cronbach coefficient (Yat the diagonal. All correlations are significant at p < 0.05.

Intercorrelations
Most of the correlations among the innovation strategy variables (X1-X6) were positive, suggesting that innovation strategy dimensions reinforced one another. We observed two exceptions (Table 1) . The association between leadership position and the use of external sources was negative. Also, the association between external sources and process innovation was negative, implying that companies deemphasized this source in pursuing process innovation.

Simultaneous Efect of Innovation Strategy on Company Performance
Multiple-regression analysis provided a test of the simultaneous effect of innovation strategy dimensions on company performance. Table 2 displays the standardized regression coefficients ( ps), which are more stable than nonstandardized coefficients and thus facilitate reliable interpretations of the results. Multiple-regression analysis was significant at p < 0.00 1, with R2 of 0.30, showing that innovation strategy was a major correlate of CFPF. The moderate R2 found in this study was consistent with past research findings in this area. For example, Johnson, Hoskisson, and Hitt ( 1993) reported a simple correlation of 0.30 between R&D investment and a measure of company performance. Research using the PIMS database

TABLE 2 Results of Multiple Regression: Simultaneous Eflect of Innovation Strategy Dimensions on Company Performance Variables X1 -Leadership orientation X2-Process innovation X3-Product innovation X4-External source X5-Internal source X6-investment level R2 F value a Standardized regression coefficient (p). * p < 0.05; **p < 0.01; ***p < 0.001. Company Financial Performances 0.33*** 0.28** 0.21* 0.09 0.24** 0.23** 0.30 27.31

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has yielded similar correlations (Buzzell and Gale 1987). These moderate coefficients may reflect short-term relationships between the variables. Conversely, long-term relationships may be stronger (Frank0 1989) because it takes time for innovation strategy variables to influence company performance. The current database does not permit an examination of such lagged relationships. It should also be acknowledged that the CFPF is a complex construct that is subject to many influences from variables that are not included in this study. Table 2 also shows that five of the six measures of innovation strategy variables were significantly associated with the CFPF (p < 0.05 or better). The exception was the external source of innovation, which had an insignificant /3. Clearly, the results supported the basic premise of the simultaneous model by showing that the dimensions of innovation strategy significantly and positively influenced company performance. Path Analysis Results In testing the sequential model, we believed that path analysis was more appropriate than other causal modeling techniques (for example, LISREL). LISREL is preferable to path analysis if the purpose of the study is to test well-established theory. MasonHawkes and Holm ( 1989, p. 3 13) state that: “LISREL iS IIIOSt Useful in refining a model after it has reached the stage of development at which all of the variables are specified and most of their relationships are known.” Path analysis is useful when the theory is not highly refined; insights from path analysis can be useful in trimming and refining theoretical models. Because the theoretical relationships among the current variables were not very well understood, we considered path analysis as appropriate. In addition, in this study, measurement errors were low-as judged by the reliability coefficients, which exceed 0.80-favoring the use of path analysis. In contrast, LISREL assumes a large measurement error in the variables. Thus, this study is consistent with established research tradition in this area, which emphasizes path analysis as the primary tool. We ran seven regressions to examine path relationships in the data. Next, we examined direct and indirect relationships in the path model. We tested the hypothesized paths using the following equations, which we derived based on the earlier discussion and which are embodied in Figure 2. X2 = a +p2,X1, X3 = a +p3rX1, X4 = a +p4,Xl, x5
= a +&*x1,

(1)
(2)

(3) (4) (5)
(6)

X6 = a + palX 1 + pe2X2 + pb3X3 + pb4X4 + psSX5, X7 = a + p7, X 1 + pT6X6.

In the analysis, a was the regression constant. The path coefficient p was defined for the path between two variables (for example, pxI was the path coefficient for the path from X 3 to X 1), defined as p; X l-X6 were the innovation strategy dimensions; and X7 was the CFPF. Figure 3 presents the results of path analysis from the regression runs. The path model was significant at p < 0.001, with an R* of 0.32, indicating that the model

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R-32
I (xs)

Investment
Level

FIGURE 3. Results of the Path Analysis Model Showing the Association Between Innovation Strategy and Company Financial Performance.

captured a significant portion of variance in the CFPF. These results were reassuring because they were consistent with our expectations. Judging by the @values in Figure 3, the hypothesized associations relating to seven of the nine links among innovation strategy measures were significant. Leadership orientation (Xl ) was significantly associated with process innovation (p < 0.001 ), product innovation ( p < 0.00 1)) internal sources (p < 0.00 1), investment level ( p < 0.00 1)) and CFPF ( p < 0.00 1) . Moreover, investment level (X6 ) was associated with product innovation (p < 0.0 1) and internal sources (p < 0.05). Further, investment level (X6 ) was associated with the CFPF ( p < 0.00 1). However, the external source (X4) was not significantly associated with either innovation leadership (Xl ) or investment (X6). The results were not unexpected becausean innovation leadership posture typically requires extensive internal developments, whereas gaining the benefits of innovation from external sources is a difficult and time consuming process (Davidson 199 1; Hitt, Hoskisson, and Ireland 1990; Hitt, Hoskisson, Ireland, and Harrison 199 1) . Decomposition of Path Variance We examined the results of the path analysis further to determine the direct and indirect effect of innovation strategy on CFPF (Li 1976; Asher 1983). A direct effect existed when a dimension of innovation strategy (e.g., Xl ) influenced company performance (X7) without the mediation of a third dimension. Table 3 displays the seven regression equations and their results. We then used the coefficients reported in Table 3 to produce Figure 3; these coefficients represented the direct paths in the model. However, to fully capture the effect of the variables on the CFPF, one must also consider their indirect effect. Indirect coefficients showed the impact of one dimension (e.g., process innovation, X2) on financial performance through its influence on a third dimension (e.g., investment level, X6). Table 4 reports the results for the direct and indirect paths. Consistent with the proposed model (displayed in Figure 2)) only two dimensions have a significant, direct effect on CFPF: Xl (leadership orientation) and X6 (invest-

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TABLE 3 Results of Path Analysis of the Innovation Strategy DimensionsCompany Performance Links Equation No. (1) ResuW x2 X3 X4 X5 X6 X7 = = = = = = 0.09 0.05 0.49 0.31 0.77 0.61 + + + + + + 0.49x1*** 0.38X1*** 0.12X1 0.44x1*** 0.34X1*** 0.41X1***

(2)
(3) (4) (5)

(6)

- 0.26X2*** + 0.33X6**

+ 0.22X3+*+ - 0.09X4 + 0.19X5’

aXl, leadership orientation; X2, process innovation; X3, product innovation; X4, external source; X5, internal source; X6, investment level. Numbers show the standardized regression coefficient (8). * p < 0.05; **p < 0.01; ***p < 0.001.

ment), both at p < 0.00 1. Further, process (X2), product (X3), and the intern& source of innovation (X5) each indirectly explained 8 percent or more of the variance in CFPF. The indirect effects of leadership orientation (Xl ) and the external source (X4) were negligible.
6. Discussion and Implications

Three findings emerge from the current study. First, the results of both the simultaneous and sequential models support the importance of innovation strategy as a correlate of company financial performance. Although causal attributions about innovation strategy cannot be made because of this study’s cross-sectional data, it appears that commitment to a strategy of manufacturing innovation pays off by improving company performance. These results support the call for companies to map a carefully designedinnovation strategyto achievesuccess today’s marketplace in (Kamm 1987; West 1992). Second, the results support the importance of the four different dimensions of innovation strategy. With the exception of the external source of innovation, components of innovation strategy are associatedpositively with and explain a significant portion of variance in CFPF. This suggeststhat companies that purposefully manage manufacturing innovation activities through a formal strategy can improve their financial performance (Grossi 1990). The present study also tests the combined
TABLE 4 Decomposition of Variance Variables XI -Leadership orientation X2-Process innovation X3-Product innovation X4-External source X5-Internal source X6-Investment level Direct Effect 0.41 0.33 Indirect Effect 0.03 -0.08 0.08 0.01 0.08 Total O&P” -0.08 0.08 0.01 0.08 0.33***

*** p < 0.001.

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effect of innovation strategy on company financial performance. This comprehensiveness is generally lacking in the literature. Most past studies have focused primarily on the association between a specific dimension of innovation strategy and company performance. The results show a negative association between the external source of innovation and company performance (Table 2 ) . Because external sources are a rich source of innovations (Von Hippel 1988)) four factors may have contributed to this negative association: ( 1) executives’ may fail to adequately integrate external innovations into the firm, (2) companies may pay too much for external innovative efforts and therefore may not achieve adequate financial benefits, (3) firms may expect early results in areas that might take years to produce improvements in financial performance, and (4) companies may err in selecting external innovation sources. Regardless of the source of the negative association, the results suggest that executives should be aware of these factors when attempting to acquire innovations from external sources. Third, an important finding from this study concerns the efficacy of the simultaneous and sequential models. Each approach espouses distinct assumptions about the hypothesized relationships between innovation strategy and performance. Yet, judging by the similar R* values (Table 2 and Figure 3), both models are about the same in their overall explanatory power. Therefore, both models can be appropriate approaches for gauging the associations between the dimensions of innovation strategy and company performance. Still, the sequential model provides additional insights into the potential indirect contribution of the individual dimensions on company performance. However, we examined one set of associations that underlie the path model. As theory advances and empirical results accumulate, other paths should be explored to uncover different sequences that may yield different results. Examining these paths will also help in validating the current results.

Limitations
Our findings should be considered in light of the study’s limitations. First, the results need further validation to support the superiority of either the simultaneous or sequential approach and to ensure that the results reported here are not sample specific. Second, the current cross-sectional data do not permit the testing of causal relationships. This is a limitation because, for example, particular levels of company financial performance may encourage (or discourage) firms from pursuing particular innovation strategies as much as particular innovation strategies promote firm performance. Third, other variables may moderate the effect of the four dimensions of innovation strategy on company performance. For example, the manufacturing experience of CEOS and divisional managers have been shown to influence the implementation of innovation activities (Ettlie 1990). Also, the extent to which innovations in technology are matched by corresponding changes in administrative practices may affect the success of an innovation strategy (Ettlie 1988).

Implications for Executive Action
This study suggeststhat a manufacturing firm needs a comprehensive innovation strategy. Executives can meet this need by ensuring that their company’s strategy formulation process incorporates planning for manufacturing innovation efforts. Given that the dimensions of innovation strategy are significantly associated with company performance, executives need to pay attention to these dimensions to ensure

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that their companies’ priorities are properly defined with respect to each dimension and also to consider the effect of these dimensions on other manufacturing activities. For example, a recent study of manufacturing industries shows that when companies adopt new production technologies, they need to look beyond their direct impact on the production work force and consider their impact on the support staff (Ward, Berger, Miller, and Rosenthal 1992). A second implication for executives is the need to manage sources of innovation. The results suggestthat internal sources of innovation are significantly and positively associated with company performance. This can be interpreted as suggesting a need for managerial commitment to internal R&D and innovation efforts. This can take many forms: allocating resources, hiring and retaining qualified personnel, and providing a supportive work environment that encourages innovation activities. A third avenue for managerial action is the need to adopt an innovation “leadership” orientation; companies should be committed to developing and introducing new products and processes. This is especially true in today’s business environment. Global competition requires commitment to introducing new products and processes (Ettlie 1990). Indeed, the results show that companies should lead the development of significant product and process innovation as a means of achieving successful performance.

Research Implications
Our results support the importance of innovation strategy as a major predictor of company performance. Researchers should examine and define the domain of innovation strategy. Future research is needed to extend our definition of this domain and the operationalization of its dimensions. These future studies would benefit from employing alternative analytic techniques to establish the validity of the current findings. For instance, researchers may explore LISREL as an alternative analytic framework for testing the sequential model (Bollen 1989). Another avenue for future research is to employ objective measures to gauge innovation strategy. For instance, one might collect objective data to measure commitment to product and process innovations and a firm’s relative emphasis on internal versus external innovation orientations. Objective data may help in validating empirical indicators of innovation strategy. Future researchers would benefit from examining the possibility of a lag effect between innovation strategy and company financial performance (Teece 1988). Clearly, innovation activities take time to influence company financial performance. The lag effect will most likely be industry specific because of the nature of the industry or the influence of environmental conditions on an industry. Therefore, by determining the length of time innovation strategy takes to influence company performance, future researchers will help in guiding R&D investments and other manufacturing innovation activities. Understanding these lags would be helpful to decision makers as they plan their innovation activities. To increase the relevance of these findings, researchers should use different measures of company performance. For instance, it would be desirable to determine if innovation strategy influences growth and profitability measuresdifferently, at different times. Moreover, as suggestedearlier, researchers should explore the associations between the dimensions of innovation strategy and subjective company performance measures, which typically reflect executives’ perceptions of their companies’ standing relative to their competition. Fi-

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nally, although we investigated the effect of the investment dimensions of innovation strategy on a company’s performance, the reverse effect-high profitability leading to higher investment in innovation -should be explored in future longitudinal research. Manufacturing innovations occur at different rates in different environmental settings (Gupta and Wilemon 1990). Future researchers can enrich the literature by examining the relationship between innovation and company performance within specific contexts (e.g., growth versus decline) of particular industries. Their results would be useful in guiding decisions about the appropriate innovation strategy for specific industries. Indeed, little is known today about the different innovation strategies firms pursue in different industry or competitive environments. By delineating these strategies, scholars can advance theory building on the ways companies respond to competitive forces and changes in their external environments. In conclusion, this study supports the importance of innovation strategy as a determinant of successful company financial performance. Its results show that executives (or decision makers) and their companies can gain considerably from articulating and adopting a comprehensive strategy for their manufacturing innovation activities. The gains that materialize from such a strategy can enhance a company’s growth and profitability. ’
’ We acknowledge with appreciation the comments of an associate editor and two anonymous reviewers of this paper.

Appendix. Innovation Strategy Dimensions We collected data for innovation strategy using multiple items. We then summed the responses to these items to produce overall indices whose reliabilities we tested using Cronbach coefficient CX,as presented at the diagonal of Table 1. The items follow. 1. Leadership Orientation. Executives rated their company’s leadership on innovation activities. We asked them to circle the one number that best described their company’s situation over the past 3 years, using the scale below. 1 Little Emphasis 2 3 Neutral 4 5 Major Emphasis

Your company’s a. emphasis on being first to introduce new products to the market b. emphasis on commercializing new products or technological models c. commitment to conducting cutting edge research and development (R&D) d. reputation for being the industry’s leader in pioneering product changes e. ability to introduce new products ahead of the competition f. emphasis on adopting a strategy of being the industry leader in offering new products (technologies)

1 1 1 1 1 1

2 2 2 2 2 2

3 3 3 3 3 3

4 4 4 4 4 4

5 5 5 5 5 5

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2. Process Innovation. Executives rated their companies’ emphasis on the following items over the past 3 years. We asked them to circle the one number that best described their companies’ situation, using the scale below. 1 2 3 4 5 Minor Major Emphasis Emphasis Your company’s emphasis on a. developing new production methods and procedures b. introducing more new methods of production than its major competitor c. introducing more new methods of production than 3 years ago d. introducing more new methods of production than your industry average 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5

3. Product Innovation. Executives rated their companies’ emphasis on and commitment to product innovation activities over the past 3 years, using a five-point scale. 1 Very Low 2 Low 3 Average 4 High 5 Very High 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 5 5 5 5 5

Your company’s a. level of product innovation b. emphasis on modifying existing products c. commitment to introducing more products than its major competitors d. commitment to introducing more products than your industry average e. commitment to introducing more products than 3 years ago

1 1 1 1 1

4. External Innovation Source. Executives rated their companies’ emphasis on the following items over the past 3 years. We asked them to circle the one number that best described their companies’ situation. 1 Minor Emphasis Your company’s emphasis on a. using products developed outside your company b. purchasing technologies developed by other firms c. acquiring products/technologies through licensing agreements d. acquiring products/technologies through joint ventures with other firms 1 1 1 1 2 2 2 2 3 3 3 3 2 3 4 5 Major Emphasis 4 4 4 4 5 5 5 5

5. Internal Innovation Source. Executives rated their companies’ emphasis on four items, covering the past 3-year period. We asked them to circle the one number that best described their companies’ situation. 1 Minor Emphasis The extent of your company’s a. reliance on internal R&D efforts in developing new products and technologies b. investment in developing new products and technologies internally c. reliance on proprietary technology d. maintaining a highly skilled R&D unit for product/technology development 2 3 4 5 Major Emphasis

1 1 1 1

2 2 2 2

3 3 3 3

4 4 4 4

5 5 5 5

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Executives rated their companies’ commitment to different aspects of innovation 6. Investment. activities over the past 3 years by circling the one number that best described their opinion, following a five-point scale. 1 Very
LOW

2 Low

3 Average

4 High

5 Very High 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 5 5 5 5 5

Level of your company’s spending on a. R&D activities b. R&D activities compared with the industry’s average c. R&D activities compared with your major competitors d. R&D staff and equipment e. R&D compared with 3 years ago

1 1 1 1 1

Company Financial Performance. The study focused on profitability (net profit margin and return on assets)and growth (growth in sales) measures of company performance. Executives provided data on their companies’ performance over the past 3-year period, as follows:

1. Your company’s average net profit margin (defined as income after taxes and interest divided by net sales) over the past 3 years: 2. Average growth in your company’s sales (defined as the percent change in your company’s net sales) over the past 3 years: 3. Your company’s average return on assets (defined as income after taxes and interest divided by total sales) over the past 3 years:

References
AMBROSIO, E. M. ( 1991), “Guidelines for the Design of an Innovative Strategy,” Znternational Journal of Technology Management, 6, 2, 113- 122. ANDERSON,J., CLEVELAND,G., AND SCHROEDER, ( 1989), “Operations Strategy: A Literature Review,” R. Journal of Operations Management, 8, 2, 133- 158. ASHER, H. B. ( 1983), Causal Modeling, 2nd ed., Sage Publications, Beverly Hills, CA. BETZ, F. ( 1987), Managing Technology: Competing Through New Ventures, Innovations and Corporate Research, Prentice-Hall, Englewood Cliffs, NJ. BIGONESS,W. AND PERREAULT, W., JR. ( 1981), “A Conceptual Paradigm and Approach for the Study of Innovators,” Academy of Management Journal, 24, 1, 68-82. BIRLEY, S. AND WESTHEAD, P. ( 1990), “Growth and Performance Contrasts Between ‘Types’ of Small Firms,” Strategic Management Journal, 11, 7, 535-557. BOLLEN, K. A. ( 1989), Structural Equations with Latent Variables, John Wiley & Sons, New York. BURGELMAN, R. A., AND SAYLES, L. R. ( 1986), Inside Corporate Innovation, Free Press, New York. BUTLER, J. E. ( 1988), “Theories of Technological Innovation as Useful Tool for Corporate Strategy,” Strategic Management Journal, 9, 1, 15-30. BUZZELL, R. AND GALE, B. ( 1987), The PZMS Principles: Profit Impact of Market Strategy, Free Press, New York. CARAVATTI, M-L. ( 1992), “Why the United States Must Do More Process R&D,” Research-Technology Management, 35, 5. 8-9. CHANEY, P. K. AND DEVINNEY, T. M. ( 1992), “New Product Innovations and Stock Price Performance,” Journal ofBusiness Finance & Accounting, 19, 5, 677-695. COVIN, J. AND PRESCOTT,J. ( 1990), “Strategies, Styles, and Structures of Small Product Innovative Firms in High and Low Technology Industries,” Journal of High Technology Management Research, 1, 1, 39-56. DAFT, R. L., SORMUNEN, J., AND PARKS, D. ( 1988), “Chief Executive Scanning, Environment Characteristics, and Company Performance; An Empirical Study,” Strategic Management Journal, 9, 2, 123-140. DAVIDSON, K. M. ( 1991), “Why Acquisitions May Not Be the Best Route to Innovation,” Journal of Business Strategy, 12, 3, 50-52. DESS,G. G. ( 1987), “Consensus on Strategy Formulation and Organizational Performance: Competitors in a Fragmented Industry,” Strategic Management Journal, 8, 3, 259-277.

INNOVATION

STRATEGY

FOR COMPANY

FINANCIAL

PERFORMANCE

35

DEVINNEY, T. M. ( 1992), “New Product and Financial Risk Changes,” Journal of Product Innovation Management, 9, 3, 222-23 I. DOSI, G. ( 1988), “Sources, Procedures, and Microeconomic Effects of Innovation,” Journal ofEconomic Literature, 26, 3, 1120-I 171. ETTLIE, J. E. ( 1983), “Organization Policy and Innovation Among Suppliers to the Food Processing Sector,” Academy of Management Journal, 26, 1, 21-44. ETTLIE, J. E. ( 1988), Taking Charge OfManufacturing, Jossey-Bass, San Francisco, CA. ETTLIE, J. E. ( 1990), “What Makes a Manufacturing Firm Innovative?” Academy of Management Executive, 4, 4, 7-20. ETTLIE, J. E., BRIDGES,W., AND O’KEEFE, R. ( 1984), “Organization Strategy and Structural Differences for Radical Versus Incremental Innovation,” Management Science, 30,4, 682-695. ETTLIE, J. E:AND REZA, E. M. ( 1992), “Organizational Integration and Process Innovation,” Academy of Management Journal, 35,4, 795-821. FINKIN, E. F. ( 1983), “Developing and Managing New Products,” Journal of Business Strategy, 3, 4, 39-46. FOSTER,R. ( 1986), Innovation; The Attacker’s Advantage, Summit Books, New York. FRANKO, L. G. ( 1989), “Global Corporate Competition: Who’s Winning, Who’s Losing, and the R&D Factor as One Reason Why,” Strategic Management Journal, 10, 5,449-474. GERWIN, D. AND TARONDEAU, J. ( 1982), “Case Studies of Computer Integrated Manufacturing Systems: A View of Uncertainty and Innovation Processes,” Journal of Operations Management, 2,2,8799. GHOSHAL, S. AND BARTLETT, C. A. ( 1988), “Creation, Adoption, and Diffusion of Innovations by Subsidiaries of Multinational Corporations,” Journal of International Business Studies, 19, 3, 365-388. GIBSON, C. H. AND BOYER, P. A. (1979), Financial Statement Analysis, Kent Publishing Company, Boston, MA. GOLD, B. ( 1987), “Approaches to Accelerating Product and Process Development,” Journal ofProduct Innovation Management, 4, 2, 8 l-88. GROSSI,G. ( 1990), “Promoting Innovation in a Big Business,” Long Range Planning, 23, 1,4 l-52. GUPTA, A. K. AND WILEMON, D. L. ( 1990), “Accelerating the Development of Technology-Based New Products,” California Management Review, 32, 2, 24-44. HAYES, R. H. AND ABERNATHY, W. J. ( 1980), “Managing Our Way to Economic Decline,” Harvard Business Review, 58, 3, 67-77. HAMBRICK, D. C. AND MACMILLAN, I. C. ( 1985), “Efficiency of Product R&D in Business Units: The Role of Strategy Context,” Academy of Management Journal, 28, 3, 527-547. HAMBRICK, D. C., MACMILLAN, I. C., AND BARBOSA, R. R. (1983), “Business Unit Strategy and Changes in the Product R&D Budget,” Management Science, 29, 7,757-770. HILL, C. ( 1992), “Strategies for Exploiting Technological Innovations: When and When Not to License,” Organization Science, 3, 4, 428-44 1. HITT, M. A., HOSKISSON,R. E., AND IRELAND, R. D. ( 1990), “Mergers and Acquisitions and Managerial Commitment to Innovation in M-Form Firms,” Strategic Management Journal, 11, 3, 29-47. HITT, M. A., HOSKISSON,R. E., IRELAND, R. D., AND HARRISON, J. S. ( 1991), “Are Acquisitions a Poison Pill for Innovation?” Academy of Management Executive, 5, 1,22-34. HOFER, C. W. ( 1983 ) . “ROVA: A New Measure for Assessing Organizational Performance” in Advances in Strategic Management, Charles Lamb (ed.), JAI, Greenwich, CT, 54-56. HOSKISSON,R. 0. AND JOHNSON, R. A. ( 1992), “Corporate Restructuring and Strategic Change: The Effect on Diversification Strategy and R&D Intensity,” Strategic Management Journal, 13, 8, 625-634. JOHNSON, R. A., HOSKISSON,R. O., AND HITT, M. A. (1993), “Board of Directors Involvement in Restructuring: The Effect of Board versus Management Controls and Characteristics,” Strategic Management Journal, 14, 3, 33-50. KAMM, J. B. ( 1987), An Integrative Approach to Managing Innovation. Lexington Books, Lexington, MA. KHAN, A. M. AND MANOPICHETWATTANA, V. ( 1989), “Innovative and Noninnovative Small Firms: Types and Characteristics,” Management Science, 35, 5, 597-66. KIM, L. ( 1980), “Organizational Structure and Innovation,” Journal of Business Research, 8, 2, 225245. KIMURA, Y. ( 1990), “Sustainable Competitive Advantages and Market Share Performances of Firms: The Case of the Japanese Semiconductor Industry,” InternationaI Journal of Industrial Organization, 8, 1, 73-92.

36

SHAKER A. ZAHRA AND SIDHARTHA

R. DAS

KRUBASIK, E. G. ( 1988), “Customize Your Product Development,” Harvard Business Review, 66, 6, 46-52. LEONARD-BARTON, D. ( 1991)) “The Role of Process Innovation and Adaptation in Attaining Strategic Technological Capability,” International Journal of Technology Management, 6, 3, 303-320. LEONG, G., SNYDER, D., AND WARD, P. ( 1990), “Research in the Process and Content of Manufacturing Strategy,” Omega, 18, 2, 109-122. LI, C. ( 1976), Path Analysis: A Primer, Boxwood Press, Pacific Grove, CA. MAIDIQUE, M. AND PATCH, P. ( 1988), “Corporate Strategy and Technological Policy” in Readings in the Management of Innovation, 2nd ed., M. Tushman and W. Moore (eds.), Ballinger Publishing Company, Cambridge, MA. MANAHAN, M. P. ( 1989), “Technology Acquisition and Research Priorization,” International Journal of Technology Management, 4, 1, 9- 19. MANSFIELD, E. ( 1988), “The Speed and Cost of Industrial Innovation in Japan and the United States: External vs. Internal Technology,” Management Science, 34, 10, 1157-I 168. MANU, F. A. ( 1992), “Innovation Orientation, Environment and Performance: A Comparison of U.S. and European Markets,” Journal of International Business Studies, 23, 2, 333-359. MASON-HAWKES, J. AND HOLM, K. ( 1989), “Causal Modeling: A Comparison of Path Analysis and LISREL,” Nursing Research, 38, 5, 3 12-3 14. MCDOUGALL, P., DEANE, R., AND D’SOUZA, D. ( 1992), “Manufacturing Strategies and Business Origin of New Venture Firms in the Computer and Communications Equipment Industries,” Production and Operations Management, 1, 1, 53-69. MCLIMORE, J., AND LARWOOD, L. (eds) ( 1988), Strategies . Successes Senior Executives Speak Out. Harper and Row, New York. PALE, M. I. ( 1988), “Management of R&D for Reduction of Technological Delay: A Strategic Viewpoint,” R&D Management, 16, 2,97-102. PEARSON,A. W. (1990), “Innovation Strategy,” Technovation, 10, 3, 185-192. PENNINGS,J. M. AND HARIANTO, F. ( 1992), “Technological Networking and Innovation Implementation,” Organizational Science, 3, 3, 356-382. PORTER, M. E. ( 1980), Competitive Strategy, Free Press, New York. PORTER, M. E. ( 1985), Competitive Advantage, Free Press, New York. QUINN, J. ( 1986), “Innovation and Corporate Strategy: Managed Chaos” in Technology in the Modern Corporation: A Strategic Perspective, M. Horwitch (ed.), Pergamon Press, New York. RAMANUJAM, V. AND VENKATRAMAN, N. (1987), “Planning System Characteristics and Planning Effectiveness,” Strategic Management Journal, 8, 5,453-468. ROBINSON, W. T. ( 1990), “Product Innovation and Start-Up Business Market Share Performance,” Management Science, 36, 10, 1279-1289. ROSENTHAL, S. R. ( 1984)) “Progress Toward the ‘Factory of the Future.’ ” Journal of Operations Management, 4, 3, 203-229. SCHENDEL, D. E. AND HOFER, C. W. ( 1979), Strategic Management: A New View of Business Policy and Planning, Little, Brown and Company, Boston, MA. SCHROEDER,R. G., ANDERSON, J. C., AND CLEVELAND, G. ( 1986), “The Content of Manufacturing Strategy,” Journal of Operations Management, 6, 4, 405-415. SKINNER, W. ( 1984), “Operations Technology: Blind Spot in Strategic Management,” Interfaces, 14, 1, 116-125. SWAMIDASS, M. ( 1986), “Manufacturing Strategy: Its Assessment and Practice,” Journal of Operations P. Management, 6,4,47 l-484. SWAMIDASS,P. M. AND NEWELL, W. T. ( 1987), “Manufacturing Strategy: Environmental Uncertainty and Performance: A Path Analytic Model,” Management Science, 33,4, 509-524. TEECE,D. J. ( 1988 ) , “Capturing Value from Technological Innovation: Integration, Strategic Partnering, and Licensing Decision,” Interfaces, 18, 3,46-6 1. THOMPSON, J. H., AND EWER, S. R. ( 1989), “How Should R&D Report Its Expenditures?’ Research and Development, 3 1, 2, 174- 176. THUROW, L. C. ( 1992), Head to Head: The Coming Economic Battle among Japan, Europe, andAmerica, William Morrow and Company, Inc., New York. VAN DEN KROONENBERG,H. H. ( 1989), “Getting a Quicker Payoff from R&D,” Long Range Planning, 22, 5, 5 l-58. VENKATRAMAN, N. ( 1989), “The Concept of Fit in Strategy Research: Toward Verbal and Statistical Correspondence,” Academy of Management Review, 14, 3,423-444. VON HIPPEL, E. ( 1988), The Sources of Innovation, Oxford University Press, New York.

INNOVATION

STRATEGY FOR COMPANY FINANCIAL

PERFORMANCE

37

WARD,P.,BERGER,P.,MILLER,J.,ANDROSENTHAL, S.(1992),“ManufacturingProcessTechnology and Support Staff Composition: An Empirical View of Industry Evidence,” Production and Operations Management, 1, 1, 5-2 1. WEST, A. ( 1992), Innovation Strategy, Prentice Hall International, London. YOUNG, J. W. ( 1977), “The Function of Theory in a Dilemma of Path Analysis,” Journal of&plied

Psychology,22, 1, 108-I 10.



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