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The Electronic Journal of Communication / La Revue Electronique de Communication

Volume 10 Numbers 1 and 2, 2000

Organizational Innovation



C. B. Crawford
Fort Hays State University

C. Sue Strohkirch, Ph.D.
Fort Hays State University

    Abstract. The effects of innovation on leadership abilities have not been widely investigated. Although diffusion of innovation theory has existed for some time, there is a need for other perspectives. In a survey (n = 292) of various organizational members, innovation was significantly related to transformational leadership abilities. The relationship between innovation and transactional leadership was not significant, and the relationship with laissez-faire leadership was inverse and significant.



Hiemstra (1983) suggested that the adoption of information technologies is one of the most anticipated events in work life. Technological changes have had a major effect on how business is done and on the managerial utilization of communication. Using personal computers has turned training, research and development, and leadership into even larger organizational commitments. Computerization has changed the way people do their jobs and, even the way people look at work (Kling & Dunlop, 1993). Today’s organization is different in structure and function due to the integration of new technology. We lack theory concerning influence strategies and how they relate to innovation and forms of leadership. This study explores the changes in how people introduce innovation and the leaders that work with these innovations. We lack theory concerning new communication technologies (Steinfeld & Fulk, 1990). Without theory, research on innovation and new technologies will lack foundation.

Theory of the Diffusion of Innovation

Innovation is a social process as well as an individual process (Goodman, Griffith, & Fenner, 1990; Van de Ven, 1986). Innovation is planned, executed, and evaluated by people. It is also social, since people rarely adopt without others adopting. Research about innovation assumes that technological innovation occurs within a social context. A second assumption is that innovation is a natural process; those not adopting technology are in the minority. Technological innovation is studied with a positive bias; progress is positive and reluctance to innovate stops progress. Innovation is universally good (Van de Ven, 1986). The "technological fix" implies technology can solve all social problems. The drive for technology is the fulfillment of a need (Van de Ven, 1986).

Diffusion of Innovation Research

Communication interfaces have grown faster to meet the needs of communication systems and the growing number of people interested in networking. New technology is different because of the integration of programmable machinery (Sproull & Goodman, 1990). The challenge is the useful harnessing of technology by individuals within a social context for beneficial outcomes (Biocca, 1993). Giacquinta, Bauer, and Levin (1993) indicated that whatever technology is used for, "the attitudes and activities that people need to adopt " (p. 134) are critical elements for innovation to occur. The social component shapes how technology is used; people use new technology in ways that mirror existing purposes.

Beniger (1990) took an alternative view when suggesting that computers, like organizations, are the controllers. The technology, rather than the innovator, is the determining factor. Computers facilitate organizational control through the use of preprocessing—the destruction, filtering out, or ignoring information in order to ease processing. Preprocessing gives people less information to process, making control and formal organization possible. Sproull and Goodman (1990) concluded that a technologically determinant perspective is problematic, since it only connects simple changes in technology to observable changes in social structure.

New technologies change the organization because of the way people make sense of their surroundings (Weick, 1990). Structure is a natural outcome of human action rather than action creating structure (Weick, 1969). Technology builds structure; it changes the way people interpret and act on the system (Goodman, Griffith, & Fenner, 1990; Weick, 1990). New technologies are moving organizations from emphasizing behavior and output control of employees toward premise control. It is not enough to measure employee activity; now employers are focusing on changing the attitudes of employees so measurement is unnecessary.

Rogers (1983) suggests that innovation is a communication process about something newer or better. Innovation, like communication, is not a one-way linear event. Innovation is relational and dynamic. He defined a range of personal behaviors toward innovation based on a bell-shaped curve. Behavioral categories range from an innovator (at the highly innovative end) to a laggard (at the low innovation end). Rogers (1986) explained that diffusion is the process that communicates an innovation over time among members of a social system. Thus, diffusion of innovation is both a social and individual activity. He theorized that a small number of people innovate very quickly. Next, a substantial number of individuals are early adopters. Early adopters precede the early majority who adopts a little before others in their social network. The next group, on the other side of the mean, is late adopters. Late adopters are still ahead of the final classification, the laggard. Laggards are not interested in integrating new technology. Rogers' theory helps define the range of personal behaviors in relation to innovation. His model is an appropriate foundation for empirical study and gives further basis for the quantification of personal innovativeness.

Effects and Implications of Innovation

Rogers' (1983; 1986) typology of innovation consequences includes a determination of the desirability of the consequence and provides a theoretical method of examining effects; however, a more contextual evaluative method will help determine the importance of the effects. To understand these effects three contexts must be examined: global, organizational, and individual.

The global context. Morton (1991) suggested that the marketplace of the 1990s is a turbulent business environment impacted by information technology integration. Information technology is changing the way that work is done, integrating business functions at all levels within and between organizations, causing shifts in the competitive climate in many industries. Hiemstra (1983) suggested that information technology was the central issue for all organizations. Cushman and King (1993) stated that the integration of new manufacturing, marketing, and management information technologies contributed to the emergence of the global organization. The high-speed management wave, which began in the high-tech sector, has spread outward.

The organizational context. Carroll and Prein (1994) noted that computer integration has both positive and negative consequences. Information technology allowed organizations to reassess their missions and operations, change management and organizational structure, and challenge leadership to transform organizations for the future (Morton, 1991). Markus, Bikson, El-Shinnawy, and Soe (1992) indicated that media usage differs by workgroup; people want integration of communication technologies and integration may not lead to seamless collaborative work. Schein (1994a) claimed that information technology impacts the organization’s culture and leadership. Furthermore, the culture impacts the structure and processes of the organization, which influence innovation. Innovation is partially mediated by the external constraints on technology. Allen and Hauptman (1994) posited that functional organization is replaced with project organization (teaming). If technology is manageable, people work together for a short time and if there is high interdependence, then project teaming is preferable to functional organizing. Communication and innovation play interdependent roles and communicative coordination should take place in functional or project organizations. Flexible hierarchies will allow organizations to react and adapt. Loveman (1994) suggested that overall productivity has not climbed due to expenditures on information technologies, but the future should yield more efficient use of information technology and a boost in productivity.

The personal context. Social changes occur when technology is introduced. Employees that are more successful at integrating new technology interact more frequently, are more communicatively competent, and have better listening abilities (Papa & Tracy, 1988). People who champion innovation tend to be risk takers, use more influence, use a greater variety of influence methods, and they have higher levels of transformational leadership behaviors (Howell & Higgins (1990a). Walther, Anderson, and Park (1994) posited that interpersonal dynamics partially depended on the medium. Interaction changes when different media are used. This is consistent with the research of media richness theorists (Daft, Lengel & Trevino, 1987). Walther (1994) found that computer-mediated communication groups were more socially oriented than nonelectric groups.

Crowston and Malone (1994) examined personal effects from the introduction of new technology. Increased information technology affects the content and quantity of communication patterns. Individuals using electronic communication channels have lower status differentials than people not using electronic media; using electronic communication media helps remove the occupational role identity and helps people communicate as equals. Fulk (1993) reasoned that attraction to the workgroup significantly mediated the relationship between media use and social influence. People having higher attraction to the group reported more social influence when using electronic media. Conversely, individuals with lower attraction were more interested in the richness of the media than the possibility of social influence. Finally, recent research on innovation and influence indicated that innovators used no more team or charismatic influence methods than moderate or laggard adopters (Crawford & Strohkirch, 1996; 1997). Innovators did have a higher preference for the use of reward/punishment/ manipulation influence methods.

Historically, innovation research focused more on the process of adoption as the phenomenon of interest. More recent research has been centered on the social implications of innovation. Research from Walther, Howell and Higgins, Rice, and other authors suggests that the act of innovating have definite social implications in the personal, organizational, and global context. Given the current social influence direction of modern leadership it seems reasonable that innovation may be related to person-centered leadership qualities.

Transformational Leadership Theory

The original formulation of transformational leadership theory comes from Burns (1978). At the core of transformational leadership is the concept of transformation, or change of the organization (Yukl, 1998). Transformational leadership best reflects this change (Bass, 1985).

Transformational Leadership Basics

Burns (1978) introduced the concept of transforming leadership as a process in which "leaders and followers raise one another to higher levels of morality and motivation" (p. 20). A chief element of transformation is the ability to cultivate the needs of the follower in a follower-centered (person-centered) manner. According to Burns, focusing on needs makes leaders accountable to the follower. First, Burns contended that followers are driven by a moral need, the need to champion a cause, or the need to take a higher moral stance on an issue. People like to feel that a higher organizational spiritual mission guides their motives. The second need is a paradoxical drive for consistency and conflict. Transforming leaders must help followers make sense out of inconsistency. Conflict is necessary to create alternatives and to make change possible. The process of transformation is empathy, understanding, insight, and consideration; not manipulation, power wielding, or coercion. Burns' work on transforming leadership lays the groundwork for much of the transformational movement, though many researchers generally neglect the moral aspect of Burns' work.

Tichy and Devanna (1986a) further operationalized the transformation:, "Transformational leadership is about change, innovation, and entrepreneurship" (p. viii). Transformational leadership is a process of micro-level and macro-level influence (Yukl, 1998). At the macro-level, transformational leaders must take charge of the social systems and reform the organization by creating an appropriate power situation. At the micro-level, transformational leaders must attend to the personalities in the organization to facilitate change at an interpersonal level. Tichy and Devanna, though discussing organizational transformation, assumed that transformational leaders begin with a social fabric, disrupt that environment, then recreate the social fabric to better reflect the overall business climate.

Contemporary Research on Transformational Leadership

According to Bass and Avolio (1994), organizational managers should move toward more transformational leadership behaviors to facilitate a culture that is purposeful, interdependent, and beyond self-interest. Leadership style plays a major role in creating and maintaining the culture. Transforming leadership is based on interaction and influence, not directive power acts (Barker, 1994). Leadership is a social process, ethically constrained, and emerges from crisis. Leaders are interested in collective results not maximum benefit for individual gain; collective action for collective relief. Leadership must forgo emphasizing productivity and performance and embrace a theory of change centered on human potential, common good, and interaction (Barker, 1994).

According to Howell and Avolio (1995), ethical leaders, while striving for success, also focus on the individual; they seek to develop followers, while unethical leaders wish to enslave. DuBrin (1995) contended that transformational leaders have charismatic attributes. Transformational leaders manage by inspiration while other leaders manage by directive. Charisma is not a necessary element for transformation. Transactional leaders use contingent rewards and administrative actions to reinforce positive and reform negative behaviors (Bass, 1985; 1990). A final category of leadership devised by Bass, laissez-faire leadership, is considered as opposite of transformational leadership. Laissez-faire leadership is focused on the abdication of leadership responsibilities.

Ray, Ugbah, Brammer, and DeWine (1996) discussed the attributes of maverick leaders: the crucial characteristic was the ability to make change occur. Maverick leaders fight the status quo to test the limits of the environment; helping establish a culture that expects change. Ray et al. (1996) contended that mavericks make innovation occur through several means: total destruction of the old organization, introduction of new technology, changing the physical structure, restructuring departments, or conducting training interventions. Ray et al. (1996) concluded that loose-coupled organizations tended to be more tolerant of innovation and maverick leaders. Since they create a culture of change, maverick leaders often groom other "maverick apprentices" to take their role as surrogate mavericks when the time comes. Though mavericks are very new and distinct construct from transformational leaders, they parallel innovative leadership closely, and should thus be considered.

Relationship between Innovation and Transformational Leadership

Although much is written about organizational innovation, relatively little addresses the influence of leadership on the design and implementation of information technology (Klenke, 1994). Few address the link between innovation and leadership, and even fewer address the relationship between transformational leadership and innovation. Tichy and Devanna (1986b) refer to transformational leaders as change oriented but they give little attention to the relationship between new technology and transformational leadership. Contractor and Eisenberg (1990) argued that people knowledgeable about the communication network rise faster but make no mention of the role of innovation and its impact on leadership.

Schein (1994a, 1994b) indicated that cultures could be assessed on their degree of innovativeness. Some cultures are built around information technology. Schein (1994a) hypothesized that organizations innovate to the extent people are proactive, problem oriented, and desire improvement. These characteristics are similar to the attributes of transformational leaders (Tichy & Devanna, 1986b). Schein (1994a) suggested that innovative leaders implement faster under conditions of groupism, collegial or participation, or even authoritarian methods of decision making. Participative leaders use the innovation more appropriately and sensitively. Schein (1994b) concluded that managers who viewed innovation as a method or transformation and were positively focused on information technology had more successful transitions.

According to Klenke (1994) information technology and the actions of leaders create new organizational forms. Leadership is at the center of the interaction between task demands, people, technology, and organization structure. The relationship between innovation and leadership is difficult to articulate given the variety of functional leadership behaviors and the range of information technologies. Technology and leadership have reciprocal effects on each other; a change in one leads to a change in the other.

Brown (1994) speculated that transformational leadership is needed in an evolving technological society. Our society is moving from controlled change to accelerated change nearly beyond control. Both attitude and behavior must be the target of transformational leaders. The primary reason for technological change failure was fear and the role of transformational leaders was to reform fear into motivation. He adopted a framework similar to Schein’s (1994a). Transformational leaders must meet market demands faster and better than before, given the increasingly interdependent economy (Brown, 1994).

Limited research addressed the relationship between innovation and transformational leadership. Howell and Higgins (1990a, 1990b, 1990c) contended that champions of innovation were significantly more transformational than non-champions. Champions operate in three ways: a rational method that promotes sound decision making based on organizational rules and procedures; a participative process, enlisting others’ help to gain approval and implementation of the innovation; going outside the formal channels of bureaucratic rules and engaging in the renegade process. Howell and Higgins (1990c) compiled a list of attributes of champions: high self-confidence, persistence, energy, risk taking, credible, and winning. They concluded that champions are found in all organizations and without champions "organizations may have lots of ideas but few tangible innovations" (p. 36). Their research was deficient in the methods used in identifying champion status. Their assessment device was based on qualitative peer nomination rather than self-report of attitudes or specific behavioral criteria. Future research should attempt to determine a relationship between a linear and continuous level of innovativeness and transformational and transactional leadership.

Hypothesis and Model Formation

In attempting to understand the fuller relationship between innovation and leadership one might posit the following hypotheses:

* H1: Innovation will be positively related to transformational forms of leadership.

* H1a: The technological component of innovation will be positively related to transformational leadership.

* H1b: The technological component of innovation will not be related to transactional leadership.

* H1c: The technological component of innovation will not be related to laissez-faire leadership.

* H1d: The influence component of innovation will be positively related to transformational leadership.

* H1e: The influence component of innovation will not be related to transactional leadership.

* H1f: The influence component of innovation will not be related to laissez-faire leadership.

The hypothesized relationships between innovation and leadership, if modeled, would appear as follows in Figure 1.

Figure 1 Model of Relationship between Innovation and Leadership



This research focuses on assessment of innovation and transformational, transactional, and laissez-faire leadership to find relevant relationships.


Subjects (N = 292) came from five organizational sources. The organizations have differing primary missions: an educational organization, medical organization, manufacturing organization, automobile sales and service organization, and utility organization. The utility, manufacturing, and medical facility received a full census sampling of all departments and personnel. The educational organization had a full sampling of staff members and several classes were polled as well. The automobile sales organization was based on a sample of approximately 50% of the total staff as determined by the researchers and the automobile liaison.

The median age range was 30 to 39. The sample consisted of 167 females (61.9%) and 103 male respondents (38.1%). Nearly 50% of the sample had some college education. Respondents were asked if they had a computer at work and home, the number of hours spent using their home and work computer, and if they had a recent technological innovation in the workplace. In terms of recent innovation, 161 subjects (60.1%) claimed they recently encountered an innovation (within the last six months) while 107 subjects (39.6%) did not. Sixty eight percent have workplace computers, and 61% have them at home. Seventy percent used computers more than "rarely" in the workplace while only 50% used a computer more than "rarely" at home.


Organizations with diverse missions were contacted and approval was received before procedural steps involving subjects were taken. Once contacted, organizational liaisons were informed about the instrument, confidentiality, and results of the instrument and were given a copy of the instruments. Following the meeting, the liaison contacted the researcher with a timetable for convenient implementation.

Once the subjects were selected (in those organizations not doing a full sampling) the survey battery was administered either personally or in small group sessions. Subjects were informed about the experimental nature of the instrument and informed consent was acquired from every subject. Training and simple directions were given for each instrument. Subjects were instructed to answer every question as completely as possible. Subjects were given ample time to complete the survey. Upon completion, those subjects that desired it were debriefed about the study and their contribution to the study. Following administration of the instrument battery data analysis occurred.


Two assessment instruments and limited demographic questions were administered. The first part of the survey battery was the Acceptance of Technological Innovation (Appendix A) instrument reported in the Crawford and Strohkirch (1996, 1997) studies. This instrument consists of 30 items dealing with the adoption of innovative technologies as rated on a five point Likert scale ranging from strongly agree to strongly disagree. Several items were also reverse coded. Prior research found the measure to be reliable and validity emerged from significant correlation to actual media use (Crawford & Strohkirch, 1996, 1997). A pilot test of the actual 30 item report was conducted (N=100) on an unrelated sample finding a strong level of reliability as well (a= .93). For the final project (n = 276) the alpha coefficient of the overall instrument showed it highly reliable a = .92). The 30 item instrument included two six item subscales: one for technological orientation and one considering the ability to influence others about technology. The subscales were also analyzed for reliability with both the technology subscale (a = .77) and the influence subscale (a = .75) showing modest reliability. A factor analysis of the twelve items was performed to check the stability of the factor structure but the results did not confirm the expected factor structure. One item from each of the subscales was dropped based on alpha reliability analysis. The remaining items were loaded on a second factor analysis, and the results confirmed the factor structure (Eigenvalues of 5.06 and 1.00). The reliability of the revised technology subscale was an improved a = .82, and for the revised influence subscale a = .83. In addition the total innovation measure was split into three equal groups creating a categorical variable (high, medium, low) for further analysis

The second instrument, the Multifactor Leadership Questionnaire (Version 5-S) created by Bass (1985), is a 70 item survey consisting of four subscales of transformational leadership acts (charisma, individual consideration, intellectual stimulation, and inspiration), two subscales of transactional leadership acts (contingent reward and management by exception), and one scale measuring laissez-faire leadership. Each subscale was comprised of 10 items; thus, the transformational scale contained 40 total items, the transactional subscale was comprised of 20 items, and the laissez-faire scale contained 10 items. The scale used for the MLQ has a 0 to 4 range, with 0 representing a strongly disagree rating. Subject's self-reported specific leadership attributes using five point Likert scales ranging from strongly agree to strongly disagree. The MLQ has been found to be very reliable (Howell & Higgins, 1990a) as both a self-report measure or as a measure of a superior’s performance. In the present application the MLQ was used as a self-report of transformational, transactional, and laissez-faire leadership attributes and had an a = .89 reliability score which was consistent with prior research. Subscale reliabilities ranged from a of a = .89 to a = .60. Analysis based on the subscales was deemed appropriate given the much higher reliabilities generated in prior research.


Initially, descriptive statistics will be reported for each individual variable. Results will be discussed in the order of the individual hypotheses. Subjects (N = 292) from the study came from five different companies. The organizations varied in their mission:

  1. Electric and natural gas utility
  2. Direct mail marketing company
  3. Automobile dealership
  4. Staff of an educational institution
  5. Health care facility

These organizations were sought due to their diverse employee base and their diversity in application of technology. Table 1 reports the source, frequency, percentage returned, and percentage of total by each organization. ANOVA analysis of the leadership variables demonstrated no significant differences between organization members (F = .86, n.s.), though there was a significant difference between organizations on innovation (F = 3.40; df = 4,271; p = .01).

Table 1

Sources, Frequencies, and Percentages of Returned Surveys

Organization # of Surveys Dispersed # of Surveys Returned % Returned % of Total
Organization 1 175 33 18.8% 11.2%
Organization 2 100 33 33.3% 11.2%
Organization 3 486 180 37.0% 61.2%
Organization 4 25 16 64% 5.4%
Organization 5 95 30 31.6% 10.2%
Total 881 292 33.3% 100%



Descriptive Statistics

Tables 2 and 3 show the mean, standard deviation, range, minimum, maximum, and valid number of responses for the variables emerging from the innovation and leadership measures.

Table 2

Descriptive Statistics for Innovation Variables

Variable Mean St. Dev. Range Min Max Valid N
Innovation - Categorical 1.98 .802 2.00 1.00 3.00 276
Innovation Scale 3.23 .51 3.06 1.63 4.70 276
Influence Subscale 2.92 .57 3.00 1.17 4.17 292
Technology Subscale 2.63 .66 3.33 .83 4.17 292


Table 3

Descriptive Statistics for Leadership Variables

Variable Mean St. Dev. Range Min Max Valid N
Transformational Scale 2.63 .38 2.75 1.20 3.95 202
Charisma Subscale 2.63 .47 3.00 1.00 4.00 228
Individualized Consideration Subscale 2.89 .41 2.90 1.10 4.00 234
Intellectual Stimulation Subscale 2.74 .43 2.80 1.20 4.00 233
Inspiration Subscale 2.21 .47 3.14 .86 4.00 232
Transactional Scale 2.20 .34 2.75 1.10 3.85 195
Contingent Reward Subscale 2.47 .47 2.90 1.10 4.00 198
Management by Exception Subscale 1.93 .42 3.20 .60 3.80 230
Laissez-faire Subscale 1.15 .52 3.80 .10 3.90 237



Innovation and Leadership Ability

Table 4 displays the correlations for the scales and subscales of innovation and leadership ability.

Table 4

Correlations between Innovation and Leadership Abilities

Leadership Variable Innovation Scale Influence Subscale Technology Subscale
Transformational Scale * r = 48, p = .001 * r = .55, p = .001 * r = .43, p = .001
Charisma Subscale * r = .34, p = .001 * r = .44, p = .001 * r = .35, p = .001
Individual Consideration Subscale * r = .34, p = .001 * r = .42, p = .001 * r = .29, p = .001
Intellectual Stimulation Subscale * r = .43, p = .001 * r = .46, p = .001 * r = .37, p = .001
Inspiration Subscale * r = .36, p = .001 * r = .41, p = .001 * r = .36, p = .001
Transactional Scale r = .11, p = .150 r = .14, p = .055 * r = .16, p = .025
Contingent Reward Subscale * r = .30, p = .001 * r = .32, p = .001 * r = .28, p = .001
Management by Exception Subscale * r = -.15, p = .026 * r = -.14, p = .04 r = -.05, p = .479
Laissez-faire Scale *r = -.25, p = .001 * r = -.22, p = .001 * r = -.18, p = .005

* indicates significance at standard criterion level for two-tailed test

The correlation matrix displayed in Table 4 suggests that there is a strong relationship between transformational leadership (and subscales) and innovation generally, the technical aspect of innovation, as well as the influence aspect of innovation. The smallest correlation between transformational leadership variables and innovation variables, though still significant, is r = .29. The correlation between the overall transformational leadership scale and innovation is a moderately significant r = .48, for the technology subscale the correlation is a moderate r = .43, and for the technology subscale the correlation is highly significant with an r = .55 value. All of the correlations were positive providing support for H1, H1a, and H1d. Furthermore, the relationship between the transactional leadership scale and innovation can be understood in light of the correlations listed in Table 4. Transactional leadership was not related to the overall measure of innovation or the influence subscale, but was related to the technology subscale. This finding is further complicated by the fact that the contingent reward factor was correlated, fairly significantly, to all three innovation variables. Management by exception was correlated to both the innovation scale as well as the influence subscale. These findings provided little support for retaining H1b and H1e. Finally, the relationship between the laissez-faire leadership scale and innovation was significantly negative as evidenced by the negative correlations ranging from r = -.25 (p = .001) to r = -.18 (p = .005). These findings provide support for the assumption that the innovators do not demonstrate a lack of leadership. But H1c and H1f cannot be retained given the negative correlation between innovation and laissez-faire leadership.

Regression analyses were performed to determine levels of shared variance between innovation and leadership. The influence and technology subscales were entered into a regression model to measure their effects on transformational leadership. The innovation and technology factors of innovation accounted for a highly significant 30.8% of the variance of transformational leadership (F = 43.75, df = 2, 196; p = .0001). The overall innovation measure was also entered into a regression model finding 23% of the variance of transformational leadership explained (F = 55.50, df = 1, 188, p = .0001). In terms of the shared variance with transactional leadership, neither the overall innovation measure (F = 2.09, ns) nor the influence and technology subscales (F = 2.69, ns) were predictive. For laissez-faire leadership, the overall innovation measure was significantly predictive (F = 14.45; df = 1, 220; p = .0002), accounting for 6% of the variance of laissez-faire leadership. The influence and technology subscales were also significantly predictive of laissez-faire leadership (F = 6.31; df = 2, 231; p = .002) accounting for over 5.2% of the variance of laissez-faire leadership. The negative correlations indicate that as innovation goes up, the level of laissez-faire leadership diminishes, providing support for H1. More importantly, however, as laissez-fire leadership increases, the level of innovation decreases. H1a, and H1c should be retained given the strong positive relationship between the technology component and transformational leadership and the lack of positive relationship with transactional and laissez-faire leadership. Furthermore, H1d should also be retained given similar findings. Overall, these results demonstrate a link between innovation and transformational leadership abilities.


Kling and Dunlop (1993) remind us that the current and future workplace is very different from the workplace of the past. Computerization is upon us, and further study and explanation of the attributes of this new world are warranted. Understanding the numerical relationships is not enough for building theory about the relationship between innovation and leadership.

Relationship between Leadership and Innovation

Our most notable finding regarding innovation centers on the relationship between innovation and transformational leadership. These results demonstrate a moderate to strong relationship between transformational leadership and innovation. In addition, the technology and influence subscales were related to transformational leadership, suggesting that transformation has both elements as well as the gestalt of innovation. Furthermore, transactional leadership was not significantly related to innovation, though the contingent reward element was significant across both innovation subscales as well as the overall measure. Finally, the laissez-faire subscale had a significant negative relationship to innovation. Among the most striking of the results is that 30% of the variance of transformational leadership was accounted for by the technology and influence subscale; 23% was accounted for by the overall innovation measure. For the laissez-faire measure, 6% of the variance was accounted for by overall measure, and 4% by the technology and influence subscales. These findings are significant and provide basis for further theorization on the relationship between leadership and innovation.

Prior research has established the link between transformation and champions of innovation (Howell & Higgins, 1990a, 1990b, 1990c) but little research focused on either the non-champion technocrat or the innovator without an upper-level organizational title. Given that leadership is a distributed human capacity rather than held in a position or by a person it makes sense to explore leadership in a variety of contexts, and at a variety of organizational levels. Furthermore, since others have looked at how "the" leader uses innovation, it seems reasonable to study how others engaging in leadership relationships innovate. There is good reason for the relationship between transformational leadership and innovation. Innovation shares one major characteristic with transformational leadership—change. The basic concept that underlies transformational leadership is the ability to change the current—transcend the present—to achieve a higher plane of leadership. The concept of transformation is very similar to innovation, although change is largely assumed in the innovation and technology literature. Innovation is the process of adaptation to the changing technical environment. This also requires change. Thus the relationship between these elements is not accidental or contrived. Innovators at all levels are interested in change. Conceptually, the link seems tenable and perhaps even proven anecdotally. It is gratifying to see the link supported empirically by the present research.

The negative relationship between laissez-faire leadership and innovation is also parsimonious. Laissez-faire leaders, as the opposite of transformational leaders in Bass’ (1985) definition, are stuck in the status quo. Laissez-faire means literally "leave it be," and these leaders resist change as a threat to status quo homeostasis. Given that innovation seeks to change the current state it makes sense that there would be either no relationship or a negative relationship with laissez-faire leadership. This study found that laissez-faire leadership is negatively associated with innovation. If managers are laissez-faire, then they are not interested in bringing innovation into the organizational context.

Transactional leadership was not significantly associated with innovation or the influence subscale. As will be discussed later, there was a significant relationship between transactional leadership and the technology subscale. A key element of transactional leadership is the "quid pro quo" mentality (i.e., if the workers produce then they will be rewarded, if they do not then rewards will be less). Transaction produces a less enlightened organization, with members worrying about how others can benefit them rather than how they can benefit the organization and achieve better results. Bass (1985) and Burns (1978) argued that the transactional state of leadership is immature and should be pushed aside; other methods (transformational leadership) produce more effective results. In this study there was no link between innovation and transactional leadership as expected, but there was a correlation with contingent reward, one aspect of transactional leadership. Contingent reward is strikingly similar to the reward/ punishment/manipulation influence method isolated by Crawford and Strohkirch (1997). Innovators use this less than mature form of leadership to elicit action on the part of others. The longer the innovation takes the further behind the organization will be. Perhaps the perception is that a more direct method (like contingent reward or reward/punishment /manipulation influence) will produce results faster. A second alternative is that direct methods are fallback positions; perhaps innovators feel pressure to use methods that are proven though less effective. Whatever the motive, innovators have a "dark side" when it comes to influencing others. This non-person centered, non-transformational side should be more thoroughly investigated.

Given the strength of correlation between innovation and transformational leadership, there is ample evidence to suggest that innovation and transformation share common features. Though not the same, transformational individuals are likely to also be highly innovative. This finding has serious implications for modern organizations as innovation and transformation are elements they might want to encourage. In the computer age, many organizations probably want to lead the innovation curve, or at least, not be lagging on the innovation cycle. Transformational leadership should be the path utilized for innovative results. If organizations want to be on the slower end of the innovation curve, then leaders that are highly transformational may not fit the culture since they may force innovation. A similar implication results from the interrelationship between transactional and laissez-faire leadership and innovation. Given that laissez-faire leadership and innovation are moderately negatively correlated, then innovative organizational cultures should avoid laissez-faire leadership. Furthermore, since transactional leadership was not related to innovation then innovation effects stemming from transactional leadership have not been sufficiently documented. Contingent reward behaviors and innovation, however, were moderately correlated. One may expect innovators to use transformational leadership behaviors as well as contingent reward behaviors to achieve results.

Application of Current Findings to Innovation Research

First, this research extended the work of innovation researchers like Rogers (1983, 1986) and Giacquinta et al. (1993), producing needed empirical evidence that diffusion of innovation is a real phenomenon. Based on this research one could assert that innovation is not evenly distributed in the population. Rogers makes this claim as he developed a curve of innovation, but this research demonstrates some degree of variability of the concept empirically. Furthermore, this research contextualized innovation within organizations. Little empirical organizational research delineates the process of innovation in organizations, let alone the personal differences that make innovation possible or unlikely. This research, by exploring a variety of different leadership relationships is perhaps even more valuable, given the fact that not just CEOs innovate in organizations. This research also supports the research of Rice (1987), Fulk (1993), and Markus et al. (1992) who suggested that innovation is a function of the social network; technology is simply interjected but the change comes from the adaption to technology. It is important to consider that innovators use different leadership methods, which implies a different method of communicating (Crawford & Strohkirch, 1996, 1997).

A few cautions seem necessary. First, those with advanced leadership skills innovate; those without advanced leadership skills are relegated to a subsidiary status in the acquisition and use of technology. Some are limited by their ability to purchase and use technology. People who do not see the application of technology (for whatever reason) or those who are not able to acquire and hone their leadership skills suffer. As a social condition, there must be more discussion over the process of innovation and how or why people are left out of the innovation process. Parry (1998) confirms the use of full grounded theory to research case studies of how social processes of leadership are enacted.

Furthermore, Beniger (1990) and Weick (1990) reasoned that technology and technical systems differ. Technology is the machinery and tools, but technical systems are human creations for purposes. These technical systems are created to reflect the worldview of their creator. Again, the issue of adopters and laggards emerges, but this time it occurs in the organization. Other authors (Schein, 1994a) posit that innovators and leaders have great control over the culture. When the conditions created by the technical system are imposed on the culture there could be conditions of mind control occurring.

Profiles of Innovators: Champions and "Techies"

The two innovation subscales were included to determine if people higher in technological focus or more able to influence others about innovation were different. When significant findings for the main innovation measure occurred, they also did for the subscales. The results cannot support that these are discrete innovator profile types, though some conclusions regarding each type of innovator can be advanced.

Conceptually, the concepts of the champion and maverick (though more anecdotal) are very similar to the findings regarding innovators in this research (empirical). The "champion" of innovation, as described by Howell and Higgins (1990a, 1990b, 1990c) is transformational in nature and seeks to innovate through the infusion of new technology. The champion uses direct means of influence, but is transformative, not manipulative or transactional. Behaviors of the champion make this person very similar to the Ray et al. (1996) maverick leader. The maverick leader seeks to tear down the old structure and rebuild with innovation; the defining part of mavericks is the ability to innovate and to change the organization. Our research supports the findings of Howell and Higgins as well as Ray et al. in suggesting that champions or mavericks exist. The influence subscale captures the essence of what makes champions and mavericks successful— influence. These types succeed only because of the change they promote in an organization. This change, or transformation, occurs because the influence innovator has the ability to make people understand that they can overcome the inertia of the status quo. This research adds to our understanding of the relationship between influence, innovation, and transformational leadership by suggesting that influence plays larger role than technological inclinations.

The "techie" innovator, as measured through the technology subscale of the innovation measure, was envisioned as a person that understands more about technology than the average person, but may not be able to communicate it. Although contemporary wisdom suggests that this personality type exists, we were not able to detect much difference between the "techie" and the innovator. There is a part of the innovator that uses the reward/punishment/ manipulation influence strategies. It should be expected that the "techie" would use less person-centered means to influence change. The use of direct means is not uncommon and has been found before. Whether this direct and impersonal influence method is an absolute indicator and predictor of being a "techie," unfortunately, is beyond the scope of this research.

Limitations and Implications for Future Research

The first limitation emerging from this research comes from the lack of empirical support (based on design) of the techie and the champion discrete innovator personality types. The research has clearly been moving toward a definition of the types of innovators that push new technology. These types (techie and champion) are the two types that were utilized in this study, but there may be others. Unfortunately, the method used in this research was not specific enough to add much more than than more anecdotal evidence of the discrete types of innovation. Clearly more research focus needs to be given to the discrete types of innovation, just as more research focus must be given to the overall concept of innovation. Future research should focus specifically on the relationship between transformational/influence based leadership and occurrance of techie or champion specific behaviors. Furthermore, this research needs to occur in the business world, as well as in non-profit or governmental contexts. Finally, the theories of techie and champion innovator types have been defined in enough literature to compel experimental research. Future studies should employ experimental methods to test differences between techies and champions on the occurance of transformational/infuence based leadership.

This research did not equate leadership with individuals in top management positions. We attempted to examine all individuals who perform leadership functions, regardless of rank/organizational status. Modern leadership theories recognize that leadership is not just "for the few, at the top, with the money" and that leadership is a relatinship rather than a position. We believe that the methodological choices were an appropriate expansion of the definition of leader/leadership, but realize a potential limit to generalizing beyond this study given this choice.

Concluding Remarks

Morton (1991) and Cushman and King (1993) saw the importance of information technology in the global business environment. Innovation is and will be central to doing business. Kling and Dunlop (1993) note the impact to the changing business environment —computers change our jobs and how we look at business, perhaps even the way we look at our personal and social lives. As the business environment seeks more efficiency from innovation (Loveman, 1994), the effects of innovation will be more obvious.

Rogers (1983) asserted that innovation goes on all the time in organizations, but only effective organizations use the process of innovation and the resulting effects. A fuller understanding of innovation process is needed. This project has attempted to highlight the importance of an examination of innovation in terms of leadership ability. This research has demonstrated how innovation and transformational leadership are closely related, but also how innovation and transactional and laissez-faire leadership relate.

Authors' Note:

The authors gratefully acknowledge the helpful ideas and comments of the Editor Dr. Tom Dixon and two anonymous reviewers.


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Appendix A



Directions: For each of the following statements circle your most likely response according to the following scale: SA=Strongly Agree, A=Agree, N=Neutral or no opinion, D=Disagree, SD=Strongly Disagree. Please try to answer all of the statements.

1. When it comes to getting new technology I am considered a risk-taker. SA A N D SD

2. I am often considered as "the individual to check with" before others get new technology. SA A N D SD

3. I consider myself skeptical when it comes to adopting new technology. SA A N D SD

4. My traditional values keep me from being interested in new technology. SA A N D SD

5. I often understand more about the workings of new technologies than other members of my organization. SA A N D SD

6. I generally deliberate thoroughly before adopting new technology. SA A N D SD

7. I serve as a role model for innovation: people look to me to make decisions about new technology. SA A N D SD

8. I can persuade others to innovate. SA A N D SD

9. I am generally suspicious of adopting new technological innovations. SA A N D SD

10. I will probably not adopt new technology because I believe that it harms our social fabric. SA A N D SD

11. Because I am often first to adopt new technology I may have a setback SA A N D SD

12. I can comfortably talk to others about using new technology. SA A N D SD

13. If there are problems with new technology others come to me for help. SA A N D SD

14. I can convince people of the usefulness of new technology. SA A N D SD

15. My decision to avoid new technology is personal and thought out. SA A N D SD

16. I would rather communicate electronically than face to face. SA A N D SD

17. People look to me for leadership when it comes to integrating new technology because my decisions are generally well thought out. SA A N D SD

18. I integrate technology before the average person in my network is comfortable with a new technology. SA A N D SD

19. After extensive consideration I feel that technology has more harmful effects than positive effects so I will avoid innovation. SA A N D SD

20. I may rush into technological innovation before others in my social network adopt the innovation. SA A N D SD

21. I have no technical knowledge about programming or the hardware involved in new technology. SA A N D SD

22. As a rule, I avoid adopting innovative technology because it is too risky to waste my limited time and money on. SA A N D SD

23. Influencing people to innovate new technology is difficult. SA A N D SD

24. I generally take less time to decide to introduce technological innovation than others and usually innovate before others. SA A N D SD

25. I understand more about the technical aspects of new technology than the average member SA A N D SD of my organization.

26. I feel that more people should adopt new technology so I can have a larger organization. SA A N D SD

27. I feel comfortable getting people to adopt new technologies. SA A N D SD

28. I am an advocate for increased innovation in my organization SA A N D SD

29. I generally master the use of new technology after my peers. SA A N D SD

30. I like to learn more about the technical aspects of new technology. SA A N D SD

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