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Several decades of research into innovation management have failed to provide clear and consistent findings or coherent advice to managers. In this paper, I argue that this is because innovation management `best practice' is contingent on a range of factors, and that we need better characterizations of the technological and market contingencies which affect the opportunity for,and constraintson,innovation.I reviewresearchoninnovationtogether with relevant studies from organizational behaviour and strategic management, and develop a model which may help to guide future innovation research on the relationships between environmental contingencies, organization configurations and performance. I identify uncertainty and complexity as the key environmental contingencies that influence organizational structure and management processes for innovation.
Conceptually, it is not difficult to identify the contribution innovation can make tocompetitiveness (Table 1). However, it is There is a gap between managers’ perceptions more difficult to establish a strong empirical of, and the reality of, criteria for successful relationship between innovation and perform- innovation (Cooper and Kleinschmidt 1993).
ance. For example, at firm level, the relation- For example, one study found that only 7% ships between innovation inputs and outputs is were aware of the main findings of research, and only half of these had attempted to apply weakness in the relationship may be caused the results of the research (Barclay 1992).
Moreover, the innovation processes used by random unpredictability of innovation.
firms have changed very little although the business environment has changed signifi- innovation at the level of the firm. One utilizes indicators available in the public domain, such International Journal of Management Reviews Volume 3 Issue 3 pp. 169183 Table 1. Innovation and competitive advantage Re-writing the rules of the competitive game, creating a new `value proposition' Offering a highly novel or unique product or service, premium pricing Difficulty of learning about the technology keeps entry barriers high Continuous movement of the cost/performance frontier Source: Adapted from J. Tidd, J. Bessant and K. Pavitt (2001) Managing Innovation: Integrating Technological, Market and Organizational Change, 2nd edition. Chichester: Wiley.
as R&D expenditure, number of patents and added ratio, and points out that identical R&D new product announcements. The other uses expenditures in different industries do not survey instruments to capture a broader range necessarily indicate identical innovation of indicators such as the proportion of tech- activity. Budworth (1993) proposes a similar ‘innovation ratio’ based on the ratio of cash proportion of sales or profits accounted for outlay to cash return, so that when, or if, a by products launched in the past three or five company with a portfolio of different products years. Table 2 lists the main measures used, reaches steady state, the innovation ratio will their main strengths and weaknesses, and an be equivalent to the ratio of innovation spend indication of possible levels of comparison.
to value added. On this basis, it is possible to The main conclusion from this is that there is calculate an innovation ratio for specific sec- no single best measure of innovation. Some tors and companies. For example, Budworth indicators work well for certain sectors, for calculates the ratio for the UK mechanical example, R&D for large chemical and elec- engineering sectors to be around 14%. As the trical firms, and others work well for certain value added for that sector is some 50% of fields of technology, for example, patents for turnover, this suggests that at least 7% of mechanical technologies or product announce- revenue should be devoted to innovation in order to sustain intangible assets. Concep- Measuring innovation inputs and outputs is tually, this ratio is similar to the depreciation difficult, but establishing the relationship Geroski (1994) shows that the profit margin firm performance is more problematic. Two of innovators – using matched data from the SPRU database and company accounts – is used. The first is concerned with accounting higher than non-innovators, controlling for other influences. However, the effect is rather profitability, return on investment (ROI) and small, suggesting that benefits may have been captured by users. Innovating firms are also more protected from cyclical downturns.
Many traditional accounting and financial indicators concentrate on short-term measures the relationship between profitability and of performance, and therefore may undervalue lagged indicators of capital input, marketing innovation. Kay (1993) argues that there can expenses and R&D. The main conclusion was be no long-term rationale for a firm that does a rate of return to R&D of about 33%, with an not add value, as value added is essentially the average lag of about five years. Process R&D had four times the rate of return of product outputs and the cost of inputs (including R&D but was more risky with a more variable capital). Walker (1979) uses a R&D/value Table 2. Strengths and weaknesses of measures of innovation • close to commercialization • misses in-house process • measures tacit knowledge • lack of homogeneity of Source: Patel (2000) in Tidd (2000).
The use of stock market value as a perform- reduces earnings per share (EPS) in the year of ance indicator has a major advantage over other expenditure, one of the major performance financial measures such as profits or ROI, as it criteria used by analysts (Arnold and Moizer is likely to reflect the affect of innovation 1984). Some industrialists believe that this approach systematically undervalues long-term assumes that the market value of the firm is R&D and capital expenditure. The fact that proportional to its physical or tangible capital, there is a weak correlation between company valuations, in terms of the price to earnings (P/ observed a significant (though noisy) effect, E), and expenditure on R&D suggests that the and Hall (1993) raises an important worry problem of under-valuation is industry specific, if it exists at all. The problem appears to have innovation are consistent. The valuation of R&D capital collapsed from a value of unity to between industry and its investors. Countering a quarter over the 1980s, a result that is robust the view that analysts are short sighted is the to measurement and specification tests. The importance of R&D information with 2.32 on Exchange consistently undervalues shares of a scale of seven (with 1 as the ‘best’) making it expensed (as opposed to capitalized) R&D development third with 2.36 (Pike et al. 1993).
Beyond R&D expenditure, research sug- expenditure on R&D as a proportion of sales gests a significant independent effect of (R&D intensity) has a significant positive patents on the market value of firms. Griliches affect on value added and the number of new et al. (1991) examined the relationship product announcements made, which suggests between patents and the market value of the that R&D activities contribute to increasing firm and found that, with the exception of the both the number of new products introduced pharmaceutical industry, changes in market and their value. Our research also confirms value due to changes in the patent rate were that R&D intensity has a significant positive not significant, accounting for only around 1% effect on the market to book value, which of the total fluctuations in market value.
(Sciteb/CBI 1991). Using the ratio of new generic indicator of product innovation. A product announcements to absolute R&D as a benefit of using product announcements as a proxy for research efficiency indicates that the measure of market innovation is that it lends efficiency of research also has a significant itself to an event-study methodology to link positive affect on the market to book value.
product announcements with the market value This suggests that the market also values the of a firm. For example, one study of more than efficiency of R&D, that is the organization and a thousand product announcements in the Wall Street Journal found that these had a positive affect on the share price of the originating firm market share and growth is less well under- (Chaney et al. 1991). The study found that firms introducing new products accrue around 0.75% excess market return over three days, includes data on some 3000 business units business unit, PIMS collects data on market conditions, competitive position and financial $26m (in 1972 dollars). Of course, the precise return and value of each product announce- profitability declines as the market evolves ment depends on the industry sectors: the over time as product and service differentia- highest returns were found to be in food, tion fall, and competition tends to shift to price. Conversely, high rates of market growth durable goods. The study also found that the average P/E ratio of the firms making new product announcements was almost twice that announcements. This implies that the stock market is valuing the long-term stream of (6) low or negative case flow. (Buzell and future earnings generated by the innovative firms at a much higher rate than the non-innovators.
The importance of market share varies with industry. Intuition would suggest that share financial performance identified relationships would be most important in capital-intensive between innovation measures such as expendi- ture on R&D and new product announce- where economies of scale are required.
value added and market to book value (Tidd has a much stronger impact on profitability in 2000; Tidd et al. 1996). For example, innovative sectors, that is those industries characterized by high R&D and/or marketing expenditure. For the R&D and marketing- intensive businesses, the ROI of the market many of the ‘rules’ for product development leader is on average 26 percentage points higher than the average small-share business.
Japanese manufacturers of consumer durables, In the manufacturing-intensive businesses, the such as electronics or automobiles (Clark and corresponding difference is only 12 points.
Fujimoto 1991). However, there is unlikely to This suggests that scale effects are more be ‘one best way’ to manage and organize important in R&D and marketing than in innovation, as industries differ in terms of manufacturing. In the short term, high rates of sources of innovation and the technological product introduction and high expenditure on and market opportunity, and organization- R&D are associated with lower profitability specific characteristics are likely to undermine the notion of a universal formula for success- related to long-term value enhancement of a ful innovation (Tidd 1997). For example, a business (Clayton and Turner 1998, 2000).
review of research on organizational innova-tion identified four factors which affect the management of innovation: type of innova- tion, stage of innovation, scope of innovationand type of organization (Damanpour 1991).
Several decades of research on the manage- Similarly, a review of research on innovation management calls for a re-examination of the created many insights into the innovation relative importance of organization context process, but to date have failed to provide a a n d i n d u st r y d y n a m i c s ( D r a z i n a n d comprehensive framework to guide innovation Schoonhoven 1996), an approach adopted by research or management practice. Studies of us at length elsewhere (Tidd et al. 2001).
innovation have been based on a broad range Contingency theory offers the potential to of disciplines, including management science, understand better how context affects innova- economics, geography, sociology and psych- tion management. The central concept is that no single organizational structure is effective different methods, definitions and samples.
in all circumstances, and that instead there is This diversity of research has limited the an optimal organizational structure that best fits a given contingency, such as size, strategy, task uncertainty or technology (Donaldson studies have failed to include some measure 1996). Therefore the better the fit between of performance or success, which makes it organization and contingency, the higher the difficult to translate much of the research into organizational performance (Donaldson 1999; management prescription (Tidd 2000; Tidd et Drazin and Van de Ven 1985). This relation- al. 1996). In this paper, I attempt to identify some of the emerging themes of research on innovation management, focusing on the rela- stantial body of research conducted in the tionships between environment, organization comparative case studies (Burns and Stalker Much of the research on the management of innovation has attempted to identify some generic ‘best-practice’, but most studies have Lawrence and Lorsch 1967). Clearly, one of the primary tasks of contingency research is to sectors. For example, the dominant models of technology management are derived from the influence organizational structure. According to a large number of seminal studies, three (1983, 1994), Galbraith (1994) and Galbraith and Lawler (1993) have developed these ideas consistently with organizational structure: size, technology and task uncertainty.
works, which attempt to match organizational There is a well-established body of research that has examined the relationship between formalization, specialization and firm size, the Contingency theory is strongly positivist, and has been much criticized, as it leaves little et al. 1969) being the most influential work on scope for other influences, such as managerial choice or institutional pressures (Powell and technology as a contingency, and discovered a relationship between production technology, offers some accommodation of the competing organizational structure and performance.
theories by allowing some ‘‘strategic choice’’ However, Woodward’s operationalization of within boundaries determined by contingen- technology was relatively crude, based simply on the flexibility and scale of production (1990). I will adopt a similar position here, processes, whereas Perrow (1970) developed a and will argue that contingencies do influence finer grain typology of technology, based on task analysability and variability. Lawrence innovation, but that they constrain rather than and Lorsch (1967) proposed that the rate of fully determine ‘best practice’, what I have referred to as ‘‘strategic degrees of freedom’’ differentiation and integration within an (Tidd 1993). Therefore, what remains is to organization, and found support for this in identify the most significant contingencies, their comparative study of organizational and the best configuration of organizational structures in three different sectors. Galbraith structures and management processes in each r e l a t i o n sh i p s b e t we e n e n v i r o n m e n t a l processed, which in turn influences the control contingencies, type and degree of innovation, and communication structures. More recently, Figure 1. Innovation, environment and performance.
example, as in the automobile industry. Inmarket contests, a continuous flow of Economists have long observed that industries differ in the amount of resources devoted to because product lives are short and imitation innovation, and in the rate of technological relatively easy. In this case, firms compete on the basis of creativity, cross-functional explanations for such differences focused on integration and time-to-market, for example, differences in firm size or market structure, as in the consumer electronics sector. Finally, but more recent work has emphasized the role learning in technological systems consists of of technological opportunity (Geroski 1994).
firms accumulating experience in solving the operational problems that appear in complex, networked technologies. Similarly, Langerak opportunity have been identified (Klevorick et al. (2000) identify a link between different et al. 1995): advances in scientific under- R&D knowledge domains and the Miles and standing; technological advances in other related industries; and positive feedback from prospector, analyser, defender and reactors.
prior technological advances. The relative recent research suggests that two contin- varies by sector. For example, the pharma- gencies exert a significant influence on the ceutical and semiconductor sectors both have organizational and management of innovation: strong links to basic science, the former to a narrow range of scientific fields, the latter to a 1997). A review of 21 innovation research much wider range of fields. In the food and projects concludes ‘‘environmental uncer- electronics industries, material suppliers and tainty influences both the magnitude and the nature of innovation . . . (which) suggests that sources of innovation. Customers are impor- future research should adopt environmentally tant sources of innovation in the machinery, sensitive theories of organizational innovation electrical equipment and medical instrument by explicitly controlling for the degree and the sectors. Pavitt (1990) develops a similar nature of environmental uncertainty’’ (Damanpour 1996). In particular, perceptions innovation: science based; scale intensive; of environmental uncertainty appear to affect i n f o r m a t i o n i n t e n s i v e ; a n d s u p p l i e r innovation (Hauptman and Hirji 1999; Souder et al. 1998). The second contingency, com- tunity are associated with different market plexity, is a function of the number of tech- structures, firm strategies and organizational nologies and their interactions, and recent research suggests that innovation in complex scenarios: technology races; technical parity competition; market contest; and learning in different from that in other fields (Dvir et al. 1998; Hobday et al. 2000). Uncertainty and complexity need to be differentiated, as they property, for example, focusing on scientific appear to have different management require- research excellence in target fields in the ments. Uncertainty is a function of the rate of pharmaceutical sector. In technical parity change of technologies and product-markets, competitions, the scientific and technical whereas complexity is a function of techno- knowledge is available to most firms, and logical and organizational interdependencies.
firms must compete instead by developing and For example, a firm exposed to an environ- Figure 2. Effect of uncertainty and complexity on the management of innovation.
Networked: low uncertainty, high com- require high levels of internal R&D and plexity. In this domain, project manage- linkages with the science base, whereas a firm attempting to manage complexity is likely to professional structures typical, e.g.
be imbedded in a network of collaborating organizations (Tidd 1995; Tidd and Trewhella • Complex: high uncertainty, high 1997). Complexity does not necessarily imply complexity. The presence of both high uncertainty, or vice versa (Tidd 1997). How- complexity to be associated with uncertainty increases. Figure 2 presents a simple two-by- two matrix, with uncertainty as one dimension and complexity as the other dimension. Each quadrant raises different issues and is likely to management and innovation (Hobday et require specific organizational structures and • Differentiated: low uncertainty, low complexity. In this domain, product and the environment of technology and innovation service differentiation are the key issues, marketing competencies are critical, and a product or market multi-divisional struc-ture typical, e.g. fast-moving consumer Innovative: high uncertainty, low com-plexity. In this domain, scientific or tech- The problem of not specifying the type and nological competencies are critical, and a functional structure typical, e.g. pharma- substantial obstacle to the generalizability of innovation research (Wolfe 1994). Innovation can take two basic forms: product innovation, will differ from the methods used occasionally that is changes in the products or services that to handle a radical innovation in product or an organization offers; and process innova- process. We can plot these two dimensions of tion, that is changes in the ways products and innovation of a simple matrix that defines the services are created and delivered. Sometimes space which has to be managed (Figure 3). On the dividing line is blurred, for example, in the duction, or a new service offering, but in most and processes, through to radical ‘new to the cases the distinction is useful. A second world’ innovations. Booz Allen & Hamilton (1982) categorize projects into six types: environmental contingencies are likely to be • cost reductions – process development associated with different types and degree of • repositioning – product augmentation innovation. For example, traditional models of product and process innovation life cyclessuggest a shift from product innovation to incremental innovation as an industry matures platform or generational; and derivative or important to note, because the ways in which (1997) distinguishes between two fundamental Figure 3. Innovation `space': the type and degree of innovation.
Source: Adapted from J. Tidd, J. Bessant and K. Pavitt (2001) Managing Innovation: Integrating Technological, Market and Organizational Change, 2nd edition. Chichester: Wiley.
types of innovation, sustaining innovation, collaborating organizations (Tidd 1997). Kay which continues to improve existing product (1993) refers to the sum of these structural characteristics forming the ‘‘architecture’’ of markets, and disruptive innovation, which provides a different set of functions which are likely to appeal to a very different segment of the market. Existing firms and theircustomers are likely to undervalue or ignore There is a significant body of research on the disruptive innovations, as these are likely to environment–strategy and strategy–structure appear inferior to existing technologies in terms of measures of benefit and performance.
specific issue of innovation (Dess et al. Therefore, established firms tend to be blind to the potential of disruptive innovation, ‘‘configuration’’ emerged from such research, which is more likely to be exploited by new which is more than a typology derived from evidence. A configuration is an internally existing customers will tend to reinforce consistent combination of strategy, organi- sustaining innovation, but will fail to identify zation and technology that provide superior or wrongly reject potential disruptive innova- tions. Our recent study of 50 development example, the success of the multidivisional projects in 25 firms examined the relationship structure, or M-form, is associated with a between the perceived novelty of a project and strategy of diversification into related product the structures, processes and methods used to manage the projects (Tidd and Bodley 2001).
complexity of information placed strains on We identified significant differences in terms the traditional functional structure. The various structures, processes and tools. For electrical industries has not been based on a example, heavyweight project managers and single product, process or market, and they are cross functional teams were more effective for the high-novelty projects, and customers and ‘‘extensible technologies’’ (Chandler 1966, suppliers were twice as likely to be involved 1990). The chemical industry extended into in the development and commercialization of textiles and pharmaceuticals, and the electrical the novel projects. This supports the notion that novelty is a significant factor affecting the machine tools. In contrast, the steel industry organizational and management of innovation.
is an example of non-extensible technology,which has focused on cost reduction and product improvement, rather than diversifica- tion. This suggests that the scope of thetechnology has a significant influence on Under conditions of complexity and uncer- strategy and organization (Channon 1973).
tainty, two organizational factors affect the However, the multidivisional form quickly ability of a firm to develop and commercialize became the de facto standard for large organizations, irrespective of the environment organization of the firm, specifically func- of technology. Multi-divisional firms can be tional links and the definition of business efficient innovators, measured in terms of divisions based on product–market linkages; patents and new products per unit of R&D and links with other organizations, such as expenditure (Cardinal and Opler 1993), as the structure facilitates efficient innovation within specific product-markets. Indeed, one of the benefits claimed for the M-form organization Amesse 1991). Studies have focused on the is that it offers the potential to centralize role of inter-personal relationships in the nesses, but to decentralize product develop- ment to the relevant divisions. However, in business divisions, and some on the rela- practice, the structure may limit the scope for tionships between different organizations learning new competencies: firms with fewer (Jones et al. 1998). The research community divisional boundaries are associated with a has tended to focus on the polar extremes – the strategy based on capabilities-broadening, role of the individual and strategic alliances, and has only recently recognized the need to daries are associated with a strategy based on bridge this gulf in studies of innovation capabilities-deepening (Argyres 1996). In suggests that performance at the level of bilateral relationships or dyads, and therefore business units is of much greater significance the configuration, nature and content of a than that at the corporate level: ‘‘corporate network impose additional constraints and returns will differ because their portfolios of present additional opportunities. A network business units differ . . . there is no evidence of ‘synergy’’’ (Rumelt 1991, 182). Therefore, the economic actors are influenced by the social structure makes it very difficult to identify and context in which they are embedded and how actions can be influenced by the position of cross existing business divisions (Tidd 1994, actors. A network can influence the actions of 1995). Decentralizing R&D reduces the scope its members in two ways (Gulati 1998): first, through the flow and sharing of information differences in the position of actors in the divisions will depend on the strategy and network, which both reflects and is a source of power and control imbalances. Therefore, the position occupied in a network is a matter of alternative structures to deal with complexity great strategic importance, and sources of and uncertainty, such as project-based firms power include technology, expertise, trust, and networked organizations (Gann and Salter long-standing business relationships such as suppliers, distributors, customers and com-petitors. Over time, mutual knowledge and In his seminal review of models of innovation, Rot hwe l l ( 1992) propo sed a ‘‘fi f th - generation’’ model of innovation manage- transaction costs. Therefore, a firm becomes more likely to buy or sell technology from facilitated by IT systems. More recently, the members of its network (Bidault and Fischer term ‘network’ has become widely used in 1994). The process is path dependent in the innovation research and practice, but is not sense that past relationships between actors usually clearly specified. There is little increase the likelihood of future relationships, and the term and alternatives such as ‘web’ innovation. Indeed, much of the early research and ‘cluster’ have been criticized for being too on networks concentrated on the constraints seeks to control standards by economies of preventing the introduction of ‘superior’ scale and proprietary standards in order to technologies or products by controlling supply lock-in customers and other organizations in and distribution networks (Hakansson 1995).
the network (Garud and Kumaraswamy 1993).
A network can never be optimal in any generic t e c h n ol o g y c o m p l e x o r p e r f or m a n c e uncertain, new mediating institutions are evolution. For example, Belussi and Arcangeli likely to be created (Attewell 1996). These (1998) discuss the evolution of innovation networks in a range of traditional industries in Italy. The potential to design explicitly or benefit from economies of scale in ‘rare event participate selectively in networks for the purpose of innovation, that is a path-creating consultants, systems integrators and service rather than path-dependent process, has only recently received attention (Galaskiewicz complex technologies. However, by reducing 1996). A study of 53 research networks found the initial burden on users, these mediating institutions may also reduce the potential for develops as a result of environmentalinterdependence, and – through common interests – an emergent network. However,another type of network requires some triggering entity to form and develop – a so- called ‘‘engineered’’ network (Doz et al. literature on innovation management and the 2000). In an engineered network, a nodal firm actively recruits other members to form a network, without the rationale of environ- develop a framework relating environmental contingencies, organizational configurations, innovation management and performance. My Networks are appropriate where the benefits uncertainty of the environment affects the infrastructure and standards and other network degree, type, organization and management of externalities outweigh the costs of network innovation, and that the greater the fit between governance and maintenance. Where there are high transaction costs involved in purchasing configuration, the greater the performance.
technology, a network approach may be more However, it is clear that this hypothesis must appropriate than a market model and, where be tested empirically, specifically using better uncertainty exists, a network may be superior measures of complexity and uncertainty.
to full integration or acquisition. Different Together, a better understanding of these and types of network are likely to be associated with different environmental contingencies innovation management research and clearer complex products have to interface with the and more consistent advice for management products and services of other vendors, and it practice. The goal should be to identify the is in the interest of all organizations to share organizational configurations most suited to knowledge in order to ensure compatibility. In specific technological and market environ- ments, rather than to seek a single ideal or appropriate. In contrast, a ‘closed’ network best-practice model for any context. In this respect, research on the management of inno- Channon, D. (1973). The Strategy and Structure of vation has only just begun (Tidd et al. 2001).
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