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Innovation in organizations: toward an integrated model.

Innovation in Organizations: Toward an Integrated Model


Innovation and its generator, the process of corporate entrepreneurship, are unquestionably among the hottest management topics for the 1990s. Browse through the "Management" section of your local bookstore, and you will find several books on the topics. Peruse recent issues of business periodicals, and you will find special editions devoted to the subject of innovation and several articles on corporate entrepreneurship. The dominant theme of these publications is usually a lament over the decline of innovation in United States corporations. Often accompanying these articles is a description of the spectacular rise of foreign competitors, especially the Japanese, to prominence in global markets once dominated by U.S. firms. Typically, the piece ends with a call for renewed entrepreneurship among American businesses in order to regain lost competitive advantage through innovation.

Despite the popular interest in innovation and calls for more entrepreneurial behavior on the part of U.S. companies, organizational researchers have made relatively little progress toward understanding what determines successful innovation. Commenting on the current state of innovation research, Bigoness and Perreault note that "present knowledge and understanding of the innovation process remains at the relatively undeveloped state - findings frequently have been either inconclusive or contradictory"[2, p. 68].

Generally, research efforts about innovation from an organizational perspective have focused on three major areas: (1) the external environment, (2) macro organizational characteristics, and (3) the individual characteristics of organizational managers [13, 17].

In their extensive review of the innovation literature, Tornatzky et al. note that there is empirical support for linking increased levels of innovation with environmental uncertainty and the structural characteristics of decentralization, complexity, and low levels of formal rules and procedures (informal structures)[20]. Regarding the correlations between the structural variables and innovation, Tornatzky et al. point out that little is known about the processes and behaviors that underlie the relationships. They also note that there has been little success in identifying a set of individual difference variables that have been consistently related to innovation.

An additional shortcoming of much of the current innovation research is that only one domain of variable has been included in many of the research studies. Despite calls for an integrated model of innovation, few studies have been successful in empirically testing an integrated model of organizational innovation[7,17].

New Research on Innovation

Although it should be expected that studies of the process of entrepreneurship would contribute to our understanding of innovation, generally this has not been the case. Most of the recent studies in entrepreneurship have been oriented toward analyzing the personality characteristics of individual entrepreneurs. Although a few studies of corporate entrepreneurship have emerged, most of these have focused upon the financial aspects of new venture creation.

Thus, despite the acknowledged importance of innovation to modern business firms, both managers and researchers are faced with a significant gap in knowledge about the subject. The purpose of this article is to describe the findings of a recent research study designed to analyze the relationships between a range of organizational and contextual variables and innovation in several business firms. By studying the effects of a number of variables upon innovation, this research hopes to contribute to clarifying some of the confusion surrounding current innovation studies and move toward an integrated model of innovation.

A basic assumption underlying this study is that a broad range of variables is likely to be associated with successful innovation and that these variables must be identified and analyzed together in order to determine their independent and combined effects upon innovation. Three different types of independent variable were selected for the study: environmental uncertainty, organizational structure, and innovation-related norms. Organizational structure was operationalized in three dimensions: degree of decentralization, degree of formalization, and degree of complexity. An explanation of all of these measures follows.

As cited above, the association between environmental uncertainty and organizational structure and innovation has been analyzed in previous studies although with mixed results. Increased levels of environmental uncertainty are believed to be related to increased innovation, because high rates of change in external conditions require organizations to innovate as a form of adaption[20]. Organizations must learn to modify their characteristics quickly as external environments change or compete at a disadvantage against more nimble rivals.

Organizational structure is also likely to be related to innovation simply because it provides the formal, internal context within which the process of innovation must proceed. Formal structure determines who has the authority to make innovation-related decisions and the degree of autonomy and flexibility that individual managers have to initiate new ideas. Structure also affects the direction and amount of information which is exchanged between participants in the innovations process.

The set of innovation-related norms which are included in this study are new to empirical innovation research. While formal organizational characteristics (e.g., complexity, decentralization, etc.) have been captured elsewhere in models of innovation, informal, culturally derived characteristics have not. The informal characteristics examined here reflect the degree to which organizational norms support and direct behaviors associated with the innovation process. It is important to consider informal controls on behavior in innovation research, since innovation is an unstructured problem. This means that neither the outcome nor the means of accomplishing any specific attempt to innovate can be predicted with certainty. Therefore, innovation-related problems are not amenable to solutions using formal organizational techniques, such as rules and procedures or appeals through the hierarchy.

Nevertheless, organizations that expect to be successful in innovating must somehow direct and control the process. Informal, inner directed controls, such as norms, can be an effective method of motivating and directing the solution of unstructured problems[16]. Norms have also been shown to be a means of directing organizational behaviors in accordance with the values and expectations of an organization's culture[10]. Therefore, it is not unreasonable to expect that informal, culturally derived rules (norms) will be present to motivate and direct the innovation-related behaviors of organizational members in organizations which are effective innovators. These norms, if they are shown to influence innovation outcomes, should be incorporated within existing models in order to move in the direction of providing a more comprehensive, integrated model of organizational innovation.

Evaluation Instrument

In order to evaluate the influence of the independent variables on innovation, a questionnaire was designed incorporating the five predictor variables (environmental uncertainty, decentralization, formalization, complexity, and innovation norms) a well as a measure of innovation as a dependent variable.

Environmental uncertainty has been conceptualized in terms of degree of complexity in external relations and the rate of change present among important elements of the external environment [19, 21]. Scales developed by Miller and Friesen were adapted for use in the questionnaire in order to measure each of these dimensions of environmental uncertainty[14]. Two additional items concerning the predictability of sources of raw materials and financial capital were added to the dynamism scale of Miller and Friesen.

The decentralization scale used in this research is a modification of a scale originally used by Hoagie and Aiken, which measures degree of decentralization in terms of the amount of autonomy and the frequency of participation in decisions that managers have within the organization[8]. For this research, the Hoagie and Aiken scale was modified to include only the domain of innovation-related decisions, and an additional scale, degree of influence in innovation-related decisions, was added.

Degree of formalization was measured using a scale devised by Van de Ven and Ferry [22]. It measures formalization in the following two dimensions: (1) degree to which rules and procedures exist in the organization and (2) the degree to which rules and procedures are followed in the organization. Complexity was measured using another Van de Ven and Ferry scale in which the subject reports the number of job titles within the organization as a measure of structural differentiation.

The innovation norm scale was designed and constructed specifically for this research. Forty-five innovation-related norm statements were identified using the Zaltman, Duncan and Holbek model of the innovation process as a basic framework [25]. Using the Zaltman et al. model as a guide, the innovation literature was reviewed extensively in order to identify sets of behaviors that are important for motivating and directing each stage of the innovation process. Eight dimensions of innovation-related behavior were identified around which norms were likely to exist and the forty-five norm statements were generated using these dimensions. The dimensions of innovation-related behavior as they relate to the Zaltman et al. model as shown in Table 1 on page 22.

Table : Table 1 Dimensions of Innovative Behavior Related to the Zaltman, Duncan, and Holbek Model

* Knowledge-Awareness of a Possible Innovation

.. Stimulation and recognition of the creative activities of individual organizational


.. Search for innovative ideas outside of the organization which may be applied

inside the organization

* Attitude Formation Toward the Innovation

.. Free and open exchange of information within the organization

.. Recognition of innovation as an important organizational activity

.. Open-minded consideration of new ideas regardless of their source

* Innovation Decision Process

.. Support for moderate risk taking in innovative ventures

.. Stimulating commitment for promising new ideas by providing emotional

and resource support to idea champions

* Implementation of the Innovation

.. Support for initial implementation and sustained commitment to the innovation

The content validity of the norm list was evaluated using a retranslation exercise[18]. As a result of this exercise, 11 norm statements were dropped from the list and the remaining 34 items were incorporated into the research questionnaire.

Innovation as a dependent variable was measured by counting the actual number of various types of innovations adopted over a three year period. The types of innovations counted in the number of innovations measure were: (1) new products or services, (2) new market applications of existing products or services, (3) new processes (technologies), (4) new organizational programs, and (5) new organizational structures.

Research Sample

Questionnaires were sent to the CEOs of 245 firms selected at random from four industrial directories listing firms in Western Pennsylvania and the Delaware Valley region of Pennsylvania and New Jersey. The only qualification was that each firm selected for the research sample must have been an independent business unit competing in a distinct industry. This qualification avoided including organizations whose major activity is the financial control or administration of other units. These types of organizations were judged as not likely to have much experience in the initiation and implementation of a broad range of innovation and their managers were not likely to be qualified to judge the importance of innovation to individual business units.

Each CEO was invited to complete a questionnaire but, more importantly, was asked to distribute additional copies to managers who were involved in recent attempts to innovate within the business unit.

Two-hundred and forty-five firms were selected to receive questionnaires in order to safely ensure that at least 42 usable responses were received in the research sample. Forty-two respondents were necessary to achieve a power of 0.90 and an alpha value of 0.05, given the ability to detect an effect size of 0.5 standard deviations from the population mean[11]. Usable responses were received from 55 organizations. The response rate (22.4 percent) is comparable to those reported elsewhere and yields adequate statistical power for the analyses reported below[9].

The average number of employees per respondent firm was 6,830, and the median annual sales were in the $51 to $100 million range.

Statistical Analyses

All questionnaire scales were tested for internal consistency using the standardized Cronbach alpha statistic[5]. The reliability coefficients ranged from 0.71 to 0.94, indicating relatively high levels of consistency in measurement.

The relationship between the dependent and independent variables was tested using the technique of hierarchical multiple regression. This technique permits the evaluation of the effects of each independent variable upon the dependent variable as well as providing a method for testing for possible interaction effects between the independent variables.

The results of the hierarchical regression procedure are shown in Table 2 on page 24. Both the restricted (containing only the independent variables) and the interactive regression models were significant beyond the 0.05 level. In the restricted model, the norm value (p = .038) and environmental uncertainty (p = .018) were significant beyond the 0.05 level. In the interactive model, the following independent variables were significant beyond the 0.05 level: (1) the interaction between all structural variables and environmental uncertainty (p = .002) and (2) the interaction between the structural variables alone (p = .001). The stepwise regression procedure also included the norm variable as part of the regression model; it approached significance at the 0.05 level with p = .078. No other variables were included in the final regression equation for the interactive model.

Table : Table 2 Stepwise Regression Results
 Restricted Model
 (Independent Variables Only)
 Beta Significance Partial
Environmental .359 .018 .382


Norm Value .313 .038 .339

[R.sup.2] = .256; Adjusted [R.sup.2] = .215

F = 6.193; Significant at F = .005
 Interaction Model
 Beta Significance Partial

Structure X

Environmental 1.852 .002 .490

Norm Value .244 .078 .302
Structure (1.502) .011 (.416)

[R.sup.2] = .399; Adjusted[R.sup.2] = .348

F = 7.754; Significant at F = .004

The change in [R.sup.2] between the restricted and the interactive model was evaluated for significance at the 0.05 level using the F-test. The change was significant, indicating the presence of important interactions between the independent variables of the model. Therefore, following the conventions of the hierarchical regression procedure, the interactive model will be used for all further analyses and discussion.

In order to better understand the underlying relationships contained in the interaction terms of the model, partial correlations were obtained for all of the organizational variables (decentralization, formalization, complexity, and innovation norms) with number of innovations while controlling for the effects of environmental uncertainty. The purpose of this analysis was to focus upon only the internal, organizational variables and to isolate their effects upon number of innovations. The partial correlations indicated that only two organizational variables, norm value (partial = .297, p = .028) and decentralization (partial = .261, p = .047) were significantly related to number of innovations while controlling for environmental uncertainty. The partial correlation analysis would seem to indicate that decentralization contributes most of the explained variance in the structural interaction terms.

Inferences from the Analyses

The results of the above analyses indicate that three variables are important influences on innovation in organizations. Two of these, norm value and decentralization, refer to organizational characteristics while the third, environmental uncertainty, refers to the external context of the organization.

The association between the innovation measure and environmental uncertainty and decentralization replicates the findings of some previous innovation studies[20]. The interaction between environmental uncertainty and structure supports basic innovation contingency theory in that it confirms a positive association between the number of innovations successfully adopted and the interaction between increased uncertainty and an organic structure (defined as decentralized, informal, and complex)[3,12].

In other words, organizations with organic structures are more successful in adopting innovations in relatively complex and rapidly changing industries. Moreover, the association between environmental uncertainty and innovation tends to support the perspective that uncertain environments impose the necessity of innovation on organizations as a form of adaption to changing external conditions [21]. It should be noted, however, that the correlation between uncertainty and innovation may as easily be explained by noting that frequent innovation may cause the perception among survey respondents that environments are more uncertain. Both of these dynamics are probably at work in creating the correlation between uncertainty and innovation.

Decentralization has been found to be significantly correlated with innovation in a number of studies [6,8,20]. Pierce and Delbecq state that increased rates of innovation are associated with decentralized structures because managers have more autonomy to initiate and test new ideas [17]. Moreover, managers who participate more frequently in innovation-related decisions and perceive that their input has meaning tend to develop more commitment to the new idea and support it more strongly during its development and implementation. This explanation has intuitive appeal and probably explains a large part of the strong association between decentralization and innovation.

The existence of a decentralized structure alone, however, is not likely to produce a consistent stream of successful innovations even in a highly uncertain environment. Although this study supports the association of a decentralized structure with innovation, its most important contribution is in the finding that the innovation norm set is also an important factor in explaining innovation. A decentralized structure may be a necessary condition for sustaining the process of innovation, but it is not sufficient to explain how and why organizational members initiate and support innovation. This point is elaborated below.

Zaltman, Duncan, and Holbeck describe innovation as an essentially uncertain process both in the initiation and application of new ideas[25]. Innovation requires the solution of a stream of problems which are inherently ambiguous and unstructured. The means by which these problems are to be solved cannot be specified before the solution is attempted - no set of rules or procedures can be applied to this trial and error process. Moreover, the solution to innovation-related problems is often influenced by organizational politics, which increases the difficulty of predicting the likely outcome of any innovative project[24].

In terms of expectancy theory, such uncertain conditions are not likely to produce a high level of motivation among organizational members to initiate or to support innovative activities even in a decentralized organizational environment [23]. Even if rewards are high for participating in successful innovation, the behaviors necessary to produce a success are unknown and the probability of success is highly uncertain, making innovation a very risky venture for most organizational participants. Under these conditions, most individuals are not likely to be motivated to initiate or to support innovation.

If this is the case, then how do organizations, such as 3M or Johnson and Johnson, generate the motivation and commitment necessary for sustaining successful innovation? Characteristics of organizational structure and the external environment per se do not provide an adequate answer to this question. Instead, there must be some mechanism within the organization which overcomes the inertia of the status quo and the risks of innovation to motivate organizational members to undertake and support innovative ventures.

The set of innovation-related norms, as an expression of organizational values and beliefs regarding innovation, can be one method of providing the necessary motivation and direction to engage in innovative activity. Although innovation directed behavior cannot be evaluated a priori in terms of its effect on desired outcomes or by its conformance with established procedures, it can be evaluated in terms of its consistency with norms which express organizational values about innovation. Moreover, although norms cannot be used directly to solve any specific innovation-related problem, they can guide organizational members into "appropriate," organizationally sanctioned behaviors which are believed to be effective means of carrying out the innovation process. For example, although organizational norms by themselves cannot give birth to the creative solutions necessary for successful innovation, they can help to produce a climate where information is freely shared across organizational barriers and where the creative insights of organizational members are nurtured.

The innovation norms may be considered as a means of creating "clan control" within the organization[16]. Clan control entails the motivation and direction of the activities of organizational members through implicit rules, which are learned through an organizational socialization process. These rules define what events are important and must be paid attention to and what types of behavior are appropriate responses to these events. The set of innovation norms defined in this research are "implicit rules," which define innovation as an important activity and guide the behaviors of organizational members into innovation producing rather than innovation resisting activities.

It is not surprising that current, empirically based models of innovation demonstrate findings which are often "inconclusive or contradictory"[2, p. 68]. Most of these models rely upon structural or environmental explanations of innovation, which cannot explain by themselves how consistent innovation is carried out by successful entrepreneurial organizations. If models of innovation or corporate entrepreneurship are to be of any use to practicing managers, they must include analyses of how innovation comes to be valued as an ongoing activity in successful entrepreneurial organizations. These models must also include a description of the cultural process by which innovation is motivated and directed. In order to provide these explanations, an organization's culture or ideology must be examined as well as its structure and environmental context.

Implications for Managers

This study has a number of implications for the practicing manager who wishes to stimulate a greater degree of innovation in his/her organization. The most fundamental advice is that there is no quick fix that magically creates a more innovative organization. Changing an organization's structure to make it more organic or changing reward systems to stimulate innovation are not likely to be successful in the absence of an innovation supporting culture.

Innovation is a complex social process during which a series of uncertain problems must be solved before a creative new idea can become a sustainable new product, process, or service. The successful execution of this process requires the extended interaction of many organizational members each contributing their own expertise to problem solutions. Innovation also requires the intensive exchange of information between organizational participants. For these interactions to be successful in such an uncertain undertaking, participants must share a common understanding regarding the direction and meaning of innovation to the organization. Culture, by creating shared values and beliefs, can provide the common understanding that links organizational members together in the innovation effort.

Within the innovative culture, norms must exist that encourage openness in sharing information across formal organizational boundaries. Environmental scanning activities need to be encouraged, since most innovative ideas are brought into the organization from the outside. The "not invented here" syndrome is not appropriate to the innovative organization. Managers must believe that both resource and psychological support should be given to creative, if non-conformist, organizational members, since true innovation departs from traditional organizational practices.

Finally, managers of more conservative firms should realize that the creation of a culture more supportive of innovation is a difficult, long term undertaking. It requires modifying basic organizational values, beliefs, and practices, which have been formed over a long period of successful experience. Nevertheless, cultural change is necessary if managers seek to make their organizations more innovative and thereby more capable of exploiting the opportunities of a changing marketplace.

References [1.] Baldridge, J. and R. Burnham. "Organizational Innovation: Individual, Organizational and Environmental Impacts." Administrative Science Quarterly, Vol. 20, 1975.

[2.] Bigoness, W.J. and W.D. Perreault. "A Conceptual Paradigm and Approach for the Study of Innovation." Academy of Management Journal, March 1981.

[3.] Burns, T. and S. Stalker. The Management of Innovation. London: Tavistock Publications, 1961.

[4.] Cohn, S. "Adopting Innovations in a Technology Push Industry." Research Management, September 1981.

[5.] Cronbach, L. "Coefficient Alpha and the Internal Structure of Tests." Psychometrika, Vol. 16, 1951.

[6.] Daft, R. and S. Becker. The Innovative Organization. New York: Elsevier Press, 1978.

[7.] Downs, G. and L. Mohr. "Conceptual Issues in the Study of Innovation." Administrative Science Quarterly, December 1976.

[8.] Hoagie, J. and M. Aiken. Social Change in Complex Organizations. New York: Random House, 1970.

[9.] Heberlein, T. and R. Baumgartner. "Factors Affecting Response Rates to Mailed Questionnaires." American Sociological Review, Vol. 43, 1978.

[10.] Kilmann, R. Beyond the Quick Fix. San Francisco: Jossey-Bass, 1984. California: Brooks and Cole, 1982.

[12.] Lawrence, P. and J. Lorsch. Organization and Environment. Cambridge: Harvard University Press, 1967.

[13.] McGinnis, M. and M. Ackelsberg. "Effective Innovation Management: Missing Link in Strategic Planning." Journal of Business Strategy, March 1983.

[14.] Miller, D. and P. Friesen. "Innovation in Conservative and Entrepreneurial Firms: Two Models of Strategic Momentum." Strategic Management Journal, Vol. 3, No. 1, 1982.

[15.] Nunnally, J. Psychometric Theory. New York: McGraw-Hill, 1978.

[16.] Ouchi, W. "Markets, Bureaucracies and Clans." Administrative Science Quarterly, March 1980.

[17.] Pierce, J. and A. Delbecq. "Organization Structure, Individual Attitudes and Innovation." Academy of Management Review, January 1977.

[18.] Smith, P. and L. Kendall. "Retranslation of Expectations: An Approach to the Construction of Unambiguous Anchors for Rating Scales." Journal of Applied Psychology, Vol. 47, No. 2, 1963.

[19.] Thompson, J. Organizations in Action. New York: McGraw Hill, 1967.

[20.] Tornatzky, L., J. Eveland, M. Boylan, M. Hetzner, E. Johnson, D. Roitman, and J. Schneider. The Processes of Innovation: Analyzing the Literature. Washington, D.C.: National Science Foundation, 1983.

[21.] Utterback, J. "The Process of Technological Innovation Within the Firm." Academy of Management Journal, March 1981.

[22.] Van de Ven, A. and D. Ferry. Measuring and Assessing Organizations. New York: John Wiley & Sons, 1980.

[23.] Vroom, V. Work and Motivation. New York: John Wiley & Sons, 1964.

[24.] Wilson, J. "Innovation in Organization: Notes Toward a Theory." In Thompson, J., ed. Approaches to Organizational Design. Pittsburgh: University of Pittsburgh Press, 1966.

[25.] Zaltman, G., R. Duncan, and J. Holbek. Innovations and Organizations. New York: John Wiley & Sons, 1973.

Robert D. Russell is Assistant Professor of Management and Business Policy at Rider College in Lawrenceville, New Jersey.
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Author:Russell, Robert D.
Publication:Review of Business
Date:Sep 22, 1990
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