Previous research leaves open which facets of leadership foster the
implementation of process innovations. In this study, the authors
analyze the effects of delegative-participative and
consultative-advisory leadership, respectively, on the implementation
success of process innovations. They argue that each of these leadership
behaviors entails specific advantages and risks and that therefore the
two patterns complement each other. The sample consisted of managers
from different organizations. Although the posited main effects of both
delegative-participative and consultative-advisory leadership are
confirmed, the significant interaction between these two leadership
styles has a different direction than the authors hypothesized.
Keywords: innovation; implementation; leadership; delegation;
participation; consultation
**********
Contemporary organizations need to be innovative to maintain a
competitive advantage. Thus, organizations increase their efforts to
generate and implement new products or processes in their work units.
Although the generation of ideas has been addressed extensively in the
literature (Amabile, Conti, Coon, Lazenby, & Herron, 1996), there
are very few studies that analyze the implementation of innovations
(e.g., Axtell et al., 2000) despite the fact that it is often the
implementation phase that poses the greatest challenge for
organizations. Moreover, the extant literature primarily focuses on
product innovations and not process innovations. Against the backdrop of
these shortcomings of the current literature on innovation, our study
focuses on the implementation of process innovations in organizations.
Our main question is: What facet of leadership behavior increases the
chances of successfully implementing a process innovation, and by what
mechanisms does this success come about? We focus on process
innovations--namely, novel solutions in generating goods and
services--such as the introduction of a new software, e-commerce
application, project management approach, personnel evaluation system
(e.g., 360[degrees] feedback), or goal-setting instrument (e.g.,
balanced score card).
Leadership has frequently been investigated as a determinant of
innovativeness (Burpitt & Bigoness, 1997; Manz, Bastien, Hostager,
& Shapiro, 1989; Oldham & Cummings, 1996; Scott & Bruce,
1998; Tierney, Farmer, & Graen, 1999). The results reported in this
literature are markedly heterogeneous (West, 2002). In part, this may be
due to the conceptualizations of leadership in the literature, many of
which have been unsatisfactory for predicting leadership success (Yukl,
2006). As a step forward, we suggest the analysis of the effects of two
important aspects of leadership on innovation: first,
delegative-participative leadership and second, consultative-advisory
leadership.
Theory
Implementation Success of Process Innovations as a Function of
Delegative-Participative Leadership and of Consultative-Advisory
Leadership
The main argument made here is that the implementation success of
process innovations is a function of both delegative-participative
leadership and consultative-advisory leadership (see Figure 1). We
define the implementation success of a process innovation by the degree
to which the work unit is perceived as being both more effective and
efficient after the innovation's implementation.
[FIGURE 1 OMITTED]
In theory, leadership is conducive to the implementation of
innovations to the degree that it prompts the subordinates to put novel
and fruitful ideas into action as intended (Lewis & Seibold, 1993).
Ideally, this will improve the effectiveness and efficiency of the work
unit. The first facet of leadership we study here,
delegative-participative leadership, refers to the degree to which the
subordinates (who may in turn also be leaders with respect to others)
are given the chance to influence the way in which an innovation is
implemented and how the respective process innovation is put into action
in their field of responsibility. Delegative-participative leadership
grants subordinates a say (participation) and discretionary authority
(delegation) with respect to the implementation. There is widespread
agreement that a delegative-participative leadership fosters creative,
innovative performance (Anderson & King, 1993; Axtell et al., 2000;
Manz et al., 1989; Mumford, Scott, Gaddis, & Strange, 2002).
Delegative-participative leadership raises the degree of
subordinates' perceived situational control (Krause, 2004).
Increases in perceived situational control--namely, the
subordinates' appraisal that the work setting is indeed susceptible
to change--attenuates the degree to which the changes induced by the
process innovation are perceived as threatening (Lazarus, 1991).
Granting opportunities to wield influence is likely to lead subordinates
to interpret the leadership process as being fair, thus procedurally
raising the acceptance of process innovations (cf. Brockner &
Siegel, 1996). Moreover, these processes enhance intrinsic motivation
for implementation. Increasing the degree of situational control fosters
the subordinates' motivation to initiate initiatives and assume
responsibility with respect to filling in the details of how a more
broadly defined process innovation should be implemented (Frese &
Zapf, 1994). This facilitates the adaptation of a process innovation to
a specific context and, hence, its functionality. This reasoning leads
to:
Hypothesis 1: Delegative-participative leadership is positively
associated with the implementation success of process innovations.
Furthermore, we assume that the implementation of process
innovations is enhanced by a second leadership facet,
consultative-advisory leadership. We define consultative-advisory
leadership as the degree to which the leader influences the follower by
providing advice, professional guidance, and background information
about the process innovation. By thus explicating the objectives of and
the prerequisites for the successful implementation of a process
innovation, consultative-advisory leadership enables a fine-tuning of
the subordinate's cognitive task model. Sharing background
information is one way of expressing appreciation for a subordinate
(Bauer & Green, 1996; Tyler, Degoey, & Smith, 1996), and it
facilitates the discussion of implementation-related issues. Moreover,
offering advice, professional guidance, and advisory background
information furthers a deeper understanding of the process innovation on
the part of the subordinate, in turn reducing the tasks' ambiguity.
By thus providing a sense of orientation and reducing ambiguity, it
becomes more likely that a follower will accept the innovation.
Promoting acceptance in turn increases the likelihood that a subordinate
will actively support the process innovation and contribute to the
success of its implementation. Finally, leadership that provides advice
and orientation fosters the cognitive adaptation of a process innovation
to different contexts in other work units. Thus,
Hypothesis 2: Consultative-advisory leadership is positively
associated with the implementation success of a process innovation.
Risks of Delegative-Participative Leadership and of
Consultative-Advisory Leadership and the Complementarity of the
Approaches
Delegative-participative leadership is not just connected with the
aforementioned advantages but also with specific risks (Sheremata,
2000). Subordinates may misinterpret the freedoms they have been
granted. In his or her work, a person may implement the process
innovations in ways that harm colleagues or the work unit as a whole.
Subsequently, such idiosyncratic reinterpretations can give rise to
relationship conflicts (Jehn, 1995). Moreover, it can be assumed that
delegative-participative leadership entails a higher need for
coordination. Freedoms must be clearly defined; they require
restrictions. Whereas delegative-participative leadership increases the
risk of misinterpretations concerning a process innovation,
consultative-advisory leadership can compensate the thus spawned
negative effects by providing information regarding the objective and
purpose of the process innovation.
Conversely, consultative-advisory leadership also has its risks.
For example, a subordinate may construe the leader's behavior as
patronizing, which in turn may lead to relationship conflicts (Jehn,
1995) and to reactance (Brehm, 1966). If a follower exhibits reactance,
this is likely to decrease his or her motivation to feel responsible for
implementing the process innovation. Moreover, he or she may
increasingly resist sharing his or her contextual knowledge that is
relevant to a successful implementation. As was the case with
delegative-participative leadership, leading others by providing advice
and orientation thus entails risks that need to be addressed. This could
be done by fostering the independence of the subordinate. In sum, two
points become obvious. First, both leadership patterns discussed here
are connected with advantages and risks (see Table 1).
Second, both leadership patterns are complementary. Leading others
by providing advice and orientation reduces the specific risks
associated with delegative-participative leadership, which consist of a
subordinate's mis- or reinterpretations of the process innovation.
Conversely, delegative-participative leadership attenuates the specific
disadvantages connected with consultative-advisory leadership, which
comprise displays of reactance on the part of the subordinate. Because
each of these two leadership facets can compensate the risks of the
respective other set of leadership behaviors, it is reasonable to assume
that with respect to implementing innovations, these leadership styles
will have the greatest beneficial effect when they are combined. By
contrast, if only one of these patterns is used, the results will most
likely be suboptimal. Concomitantly employing both
delegative-participative leadership and consultative-advisory leadership
brings to fruition the full positive potential of each of these
leadership styles. Thus, these behavioral patterns can be viewed as
functionally equivalent. We therefore posit,
Hypothesis 3: Consultative-advisory leadership moderates the
relationship between delegative-participative leadership and the
implementation success of product innovations. When levels of
consultative-advisory leadership are high, this relationship is
positive, whereas when levels of consultative-advisory leadership are
low, this relationship is negative.
Method
Sample and Procedure
Managers (N = 388) from German organizations of different sizes and
sectors were surveyed. The process innovations were treated as critical
incidents (Flanagan, 1954), which has the advantage of a higher context
specificity (see Krause & Kearney, 2006) and thus more valid answers
in comparison to other methods. The managers were requested to recall a
specific process innovation in their work unit and to describe this
innovation in a qualitative and quantitative manner. They were then
asked to answer questions about how they as managers were led by their
immediate superior during the innovation process and to rate the degree
to which the implementation was successful.
The managers were recruited for the study in three different ways.
First, letters were sent to randomly selected persons in leadership
positions whose names and addresses are contained in a German catalogue
(called Hoppenstedt) that features 55,700 managers. Second, at airports,
exhibitions, conferences, and leadership training courses, managers were
approached in person and asked for their participation directly. Third,
questionnaires were handed to managers by the heads of the personnel
departments of various organizations. We had business-related contacts
with those heads of the personnel departments and asked them if they
would be willing to distribute the questionnaire to the managers working
in their departments.
After a brief personal communication concerning topic and goals of
the study, the questionnaire and attached letter were either handed to
the participants directly along with a self-addressed stamped envelope
or sent via regular mail or e-mail. The questionnaires were returned
anonymously to our university via regular mail in a sealed envelope.
Participation in the study was voluntary, and no remuneration was
offered. In return for answering the questionnaire, those participants
who were interested were supplied with aggregated and anonymous
information regarding the descriptive results of the study. The strict
anonymity policy that prevented us from sending reminders to the
contacted managers who had not yet responded and the length of the
questionnaire militated against obtaining a high response rate. However,
our final response rate of 24% might indicate that selection effects of
the queried managers had occurred. Hence, we examined the possibility of
a response bias with respect to industry sector and organization size.
Contrary to what would have been expected in the case of a response
bias, our analysis revealed that our participants constituted a
sufficiently representative sample of German managers. Our results can
therefore be generalized to managers at different hierarchical levels
and in different industries and fields of specialization.
The respondents ranged in age from 22 to 64 years (M = 39 years, 6
months; SD = 9 years, 9 months) and represented several levels of
hierarchy (21% group leaders, 23% department heads, 12% division heads,
23% area heads, 16% general managers, 5% members of the managing board)
and areas of expertise (27% from marketing and sales, 22% from business
administration, 21% from personnel and organization design departments,
9% from production, 7% from research and development, 6% from technical
support, and--because of missing data--8% from unknown areas). Of the
respondents, 82% were men. This overrepresentation of men reflects the
current gender disparity in German organizations. The sectorial
distribution of the managers in the sample was broad (19% in banks and
insurance companies; 18% in telecommunications, data processing, or the
media; 16% in services; 8% in construction; 8% in mechanical engineering
and the automotive industry; 8% in trade; 5% in the chemical industry;
5% in utility companies; 2% in the food industry; and--again because of
missing data--11% from unknown industries). The distribution of the
managers with respect to the size of their respective organization
showed that most of the managers (81%) worked either in medium-sized
companies (with up to 500 employees) or large companies (with 501 to
5,000 employees).
Measures
Measurement of leadership. The instruction in the part of the
questionnaire pertaining to leadership was, "Please evaluate the
extent to which your superior used the following leadership strategies
during the innovation process." Leadership was assessed using a
6-item scale (7-point Likert scale, ranging from 1 = strongly agree to 7
= strongly disagree), whose construct and criterion validity have been
shown to be satisfactory (Krause, 2004). The leadership scale was
developed in three steps. First, we developed a pool of 82 leadership
items pertaining to process innovations. In a pretest, we calculated
item characteristics and scale dimensionality and reliability. Based on
the results of the pretest, we selected 18 items for our final
leadership scale. Second, we tested the structure of this scale in a
different sample and found five leadership components (Krause, 2004).
Third, we evaluated these five leadership facets with respect to their
relevance concerning our criterion implementation success. We identified
two leadership patterns that we consider to be most important in regard
to implementation success, namely, delegative-participative leadership
and consultative-advisory leadership.
We checked the factor structure of the employed leadership scale by
means of a principal components analysis with varimax rotation. The
results confirmed our assumption of two leadership factors, which
together explained 71% of the variance. The items of the first factor
were "During the innovation process, my superior gave me many
opportunities to contribute to shaping this innovation in my area of
responsibility;" "During the innovation process, my superior
granted me autonomy, degrees of freedom, and decision-making
authority;" "During the innovation process, my superior
presented me with a fait accompli (reversed)." This factor is
interpretable as delegative-participative leadership (Cronbach's
[alpha] = .82). The items of the second factor were "During the
innovation process, my superior helped me in solving complicated
issues;" "During the innovation process, my superior shared
with me his or her professional ideas;" "During the innovation
process, my superior provided me with all the important
information." This factor can be construed as consultative-advisory
leadership ([alpha] = .70).
Measurement of implementation success. Implementation success was
measured with four newly developed items on a 7-point Likert scale,
ranging from 1 = unsuccessful to 7 = successful. The items were
"How would you rate the overall success of the implementation of
the process innovation?" "How would you rate the success of
the implementation of the process innovation with respect to the
effectiveness and efficiency of your work unit?" "How would
you rate the success of the implementation of the process innovation
with respect to your initial hopes and fears?" "How would you
rate the success of the implementation of the process innovation with
respect to unexpected side effects?" All of these items loaded on
one factor ([alpha] = .91) that explained 79% of the variance.
Control variables. We included job tenure (which ranged from 1 year
to more than 10 years) and degree of innovation as control variables.
The respondents' job tenure can be interpreted as experience in
their jobs, which may have an impact on the level of implementation
success. Furthermore, the degree of innovation needs to be controlled
because there is reason to believe that implementation barriers rise
with increasing degree of innovation. The degree of innovation (7-point
Likert scales) was operationalized by three criteria: scope ("The
chosen new process differs strongly from the processes employed by my
organization in the past"), initiative ("My work unit was the
first to develop and/or implement this novelty"), and ramifications
("Through this novelty, the extant structures of power, control,
and competencies were altered significantly"). These items loaded
on one factor that explained 45% of the variance. The reliability of
this scale was modest ([alpha] = .60).
Results
Table 2 presents the means, standard deviations, and
intercorrelations of the study variables. As expected, both leadership
facets were significantly positively related to success regarding the
implementation of process innovations. We had argued earlier that each
of these two leadership patterns is connected with undesired secondary
effects and that the respective other strategy is necessary as a
countermeasure to compensate these negative effects. To test this
assumption, we conducted a hierarchical regression analysis of
implementation success. In the first step, we entered job tenure and
degree of innovation as control variables. We added
delegative-participative leadership and consultative-advisory leadership
in the second step of the regression. Finally, in the third step, we
entered the interaction effect of both leadership patterns. Table 3
summarizes the results.
The regression weights of the control variables were not
significant. In support of Hypotheses 1 to 3, adding
delegative-participative leadership and consultative-advisory leadership
as main effects in the second step explained a significant portion of
the variance. Entering the interaction term of both leadership
components in the third step likewise yielded a significant change in
the amount of variance explained (see Table 3). Specifically, the
interaction explained an additional 3% of the implementation success
variance over and above the variance explained by the main effects.
Together, the main effects and the interaction effect explained 30% of
the differences regarding the success of the process innovation
implementation. This is fairly substantial when considering that
effectiveness and efficiency also depend on the quality and the
potential of the process innovation itself. This amount of explained
variance is also high in light of the fact that a common method variance
might have occurred in this study--an aspect that we will discuss in the
section on limitations.
Nevertheless, although the interaction effect is statistically
significant, its direction is somewhat different than we had
hypothesized. This is a surprising result that merits closer scrutiny.
On the one hand, it appears to be the case that the highest level of
implementation is evident when the levels of both leadership patterns
are high. This is in line with our reasoning underlying Hypothesis 3:
Combining both leadership patterns enables each leadership style to
neutralize the discussed risks of the respective other set of leadership
behaviors and vice versa. In this case--namely, when the levels of both
leadership patterns are high--the respective advantages of each
leadership style can be brought to full fruition.
On the other hand however, the results show that each of the two
leadership styles is also conducive to success when the level of the
respective other leadership pattern is low (see Figures 2 and 3). This
finding contradicts our assumptions underlying Hypothesis 3.
[FIGURES 2-3 OMITTED]
Discussion
Contributions
The present study makes two contributions to the research
literature. First, with respect to successfully implementing process
innovations, it underscores the importance of the interaction between
delegative-participative and consultative-advisory leadership. Based on
a literature review of single studies and meta-analyses and personal
communication with colleagues who specialize in leadership, we think
that this is one of the few studies that examine the contribution of the
interplay of those leadership facets on implementation success. Previous
studies of innovation have only investigated one of the two leadership
components discussed here (e.g., Axtell et al., 2000) but not their
interaction. We believe however that viewing either
delegative-participative or consultative-advisory leadership in
isolation neglects the complexity of organizational leadership in
action. We therefore propose that a more complete understanding of the
factors underlying implementation success can be gained by examining the
interplay of these two sets of leadership behaviors.
Second, the results of the present study increase our knowledge of
the implementation process as we examine the conditions of successful
implementation regardless of the long-term effects of innovations. This
is important because there are very few empirical studies of the
implementation of process innovations. Nevertheless, some scholars have
focused on the implementation of innovations in general. For instance,
De Dreu (2006) showed that innovation (operationalized as the
implementation of new procedures and methods and assessed in interviews
of team supervisors) is a curvilinear function of task conflicts in
management teams. Such studies do not explain however in what ways
leadership may have either functional or dysfunctional effects on
implementation success.
Examining the Form of the Interaction Effect
Examining the form of the interaction effect we identified promises
to shed some light on important issues. Situations in which there is low
delegative-participative leadership are hardly uncommon in
organizational settings. During the implementation of process
innovations, leaders are often themselves the recipients of
nonnegotiable instructions issued by their superiors. Frequently, they
pass the thus generated pressure on to their subordinates. In this
constellation, high levels of consultative-advisory leadership may be
particularly conducive to successful implementation phases. When a
subordinate is presented with a fait accompli, providing background
information and offering advice may make it possible to develop or
retain his or her motivation to cooperate despite the clear-cut
guidelines that offer little leeway in regard to how the work is to be
done. Such leadership actions may be construed by subordinates as
considerate behavior on the part of the leader and may thus counteract
some of the negative motivational effects of centralized decisions. If
this reasoning is correct, this would mean that consultative-advisory
leadership does not act as a buffer against the risks of high levels of
delegative-participative leadership but rather serves to counter the
risks entailed by low levels of delegation and participation.
The situation is similar when there are low levels of
consultative-advisory leadership, which may also occur frequently in
organizations. Often, leaders may either not be present physically or
not have the time to offer consultations and advice. Or they themselves
may not be sufficiently informed about the details of the process
innovation. Particularly in this constellation, a
delegative-participative leadership style may enhance implementation
success because the subordinate thus receives the opportunity and the
legitimization to help himself or herself in any way that appears
expedient. Again, this would mean that delegative-participative
leadership is not a buffer against the risks entailed by high levels of
consultative-advisory leadership but rather acts as a countermeasure
against the risks of a lack of consultative-advisory leadership.
Limitations
It is important to acknowledge the limitations of the present
study. First, as is the case in most empirical studies of innovation,
all constructs were measured retrospectively and may thus be affected by
hindsight bias. Because one can assume that the degree of retrospective
distortions will increase over time, the participants were asked to
answer the questions with respect to more recent process innovations. We
thus aimed to at least reduce the degree of retrospective distortions.
To completely prevent hindsight bias effects however, longitudinal
follow-up studies would be needed.
Second, the self-report data may be affected by common method bias
(Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). To prevent this
problem, it is typically recommended that studies include different
groups of people (e.g., members of the steering committee, project
directors, developers of innovations, and users of innovations), with
each group evaluating different variables (e.g., the leadership style is
rated by the subordinates, whereas the implementation success is rated
by top managers or customers). However, Spector (2006) argued that the
potential problem of common method variance may be exaggerated. He
provided empirical evidence that calls into question the assumption that
the self-report method by itself yields systematic variance that
significantly inflates results.
Nevertheless, we have addressed this problem by calculating the
structure across all items of the study. Confirmatory factor analyses
with maximum likelihood extraction were used to assess the fit of the
general factor (G factor) model to the data in comparison to the
subfactor model. If the model test confirmed the G factor model, this
would indicate the presence of a common method bias. (In the
confirmatory model tests, a correlation matrix was used as the starting
matrix. The variances of the latent variables were fixed. All loadings
and residuals were estimated freely.) However, the data did not support
a G factor model. Several fit indices show that the G factor model does
not fit the data (Adjusted Goodness-of-Fit Index = .54, Goodness-of-Fit
Index = .64, root mean square error of approximation = .25, [chi square]
= 392.91, p < .0001). By contrast, the three-factor model fits the
data reasonably well (Adjusted Goodness-of-Fit Index = .90,
Goodness-of-Fit Index = .92, root mean square error of approximation =
.04, [chi square] = 6380.01, p < .0001).
Conclusions
Theoretical Conclusions
Our initial reasoning for the mutual risk compensation effect of
delegative-participative and consultative-advisory leadership
(Hypothesis 3) appears not to be valid in the context of process
innovations, at least in this sample. This may be so because with
respect to process innovations, the posited buffering effects occur not
so much when the levels of the two leadership patterns are high but
rather when the level of one of these leadership styles is low. In other
words, neglecting either delegative-participative or
consultative-advisory leadership behavior entails specific risks, and
these risks can be held in check by enacting high levels of the
respective other leadership pattern.
On a theoretical level, this shows that not only the relationship
between a particular leadership style and the implementation success of
innovations merits consideration but that the dynamics resulting from
the interplay of different sets of leadership behavior should also be
analyzed. One important aspect to examine would be how different
combinations of leadership patterns affect success. A better
understanding of the interplay of different leadership styles
presupposes a clear description of the risks entailed by both high
levels and low levels of the respective leadership behaviors. The
present study underscores the importance of this question by
illustrating the theoretical and practical importance not only of the
interactions of leadership behaviors but also of the specific form of
these interaction effects. The absence of one of the two sets of
leadership behaviors discussed earlier is apparently linked with
specific risks that need to be compensated by the other complementary
set of leadership measures to ensure high levels of success.
Practical Conclusions
With respect to practical implications, the present study indicates
that the quality of the implementation of process innovations and thus
the effectiveness and efficiency of the respective work unit are highest
when leaders exhibit both delegative-participative and
consultative-advisory leadership behavior simultaneously. Thus, leaders
would be well advised to combine these leadership facets. If, for
whatever reason, a leader is unable to provide both of these leadership
aspects (i.e., both delegative-participative and consultative-advisory
leadership), the importance of the respective other complementary set of
behaviors becomes all the more important during the implementation
process. Thus, at the very least, a leader should enact high levels of
one of these sets of leadership behaviors (i.e., either
delegative-participative or consultative-advisory leadership). Ideally
however, a leader should strive to employ a combination of these two
leadership styles so that the specific risks entailed by one set of
behaviors are compensated by the effects of the respective complementary
leadership pattern and vice versa.
Our results offer important implications for both leadership and
management (cf. Yukl, 2006). With respect to management however, we
would argue at a higher level of abstraction. Specifically, our results
indicate that in the effort to foster implementation success, a holistic
management perspective is called for. That is, a company's
management must not only anticipate the respective positive and negative
effects of delegative-participative and consultative-advisory leadership
but also needs to consider the effects of combinations of leadership
patterns. This entails that management acknowledges the dynamics of
leadership patterns--namely, their antagonistic and/or complementary
effects.
The usefulness of such a management approach has already been
established with respect to other outcome criteria (e.g., increasing
innovation speed, fostering innovation quality, decreasing innovation
costs, promoting team innovations, enhancing organizational change) (cf.
Atuahene-Gima, 2003; Gebert, Boerner, & Kearney, 2006; Quinn &
Cameron, 1988; Sheremata, 2000). We propose that this approach is also
conducive to successfully implementing process innovations. Hence, we
would advocate a greater emphasis on holistic leadership in management
education and training programs.
References
Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Herron, M.
(1996). Assessing the work environment for creativity. Academy of
Management Journal, 39, 1154-1184.
Anderson, N. R., & King, N. (1993). Innovations in
organizations. In C. I. Cooper & I. T. Robertson (Eds.),
International review of industrial and organizational psychology (Vol.
8, pp. 1-33). Chichester, UK: Wiley.
Atuahene-Gima, K. (2003). The effects of centrifugal and
centripetal forces on product development speed and quality: How does
problem solving matter? Academy of Management Journal, 46, 359-373.
Axtell, C. M., Holman, D. J., Unsworth, K. L., Walt, T. D.,
Waterson, P. E., & Harrington, E. (2000). Shopfloor innovation:
Facilitating the suggestion and implementation of ideas. Journal of
Occupational and Organizational Psychology, 73, 265-285.
Bauer, T. N., & Green, S. G. (1996). Development of
leader-member exchange: A longitudinal test. Academy of Management
Journal, 39, 1538-1567.
Brehm, J. W. (1966). Theory of psychological reactance. New York:
Academic Press.
Brockner, J., & Siegel, P. A. (1996). Understanding the
interaction between procedural and distributive justice. The role of
trust. In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations:
Frontiers of theory and research (pp. 390-413). Thousand Oaks, CA: Sage.
Burpitt, W. J., & Bigoness, W. J. (1997). Leadership and
innovation among teams. The impact of empowerment. Small Group Research,
28, 414-423.
De Dreu, C. K. W. (2006). When too little or too much hurts:
Evidence for a curvilinear relationship between task conflict and
innovation in teams. Journal of Management, 32, 83-107.
Flanagan, J. C. (1954). The critical incidents technique.
Psychological Bulletin, 51, 327-358.
Frese, M., & Zapf, D. (1994). Action as the core of work
psychology: A German approach. In H. C. Triandis, M. D. Dunnette, &
L. M. Hough (Eds.), Handbook of industrial and organizational psychology
(pp. 271-340). Palo Alto, CA: Consulting Psychologists Press.
Gebert, D., Boerner, S., & Kearney, E. (2006).
Cross-functionality and innovation in new product development teams: A
dilemmatic structure and its consequences for the management of
diversity. European Journal of Work and Organizational Psychology, 15,
431-458.
Jehn, K. (1995). A multimethod examination of the benefits and
detriments of intragroup conflict. Administrative Science Quarterly, 40,
256-282.
Krause, D. E. (2004). Influenced-based leadership as a determinant
of the inclination to innovate and of innovation-related behaviors--An
empirical investigation. Leadership Quarterly, 15, 79-102.
Krause, D. E., & Kearney, K. (2006). The use of power in
different contexts: Arguments for a context specific perspective. In C.
A. Schriesheim & L. L. Neider (Eds.), Power and influence in
organizations. New empirical and theoretical perspectives. Research in
management: Vol. 5 (pp. 59-86). Greenwich, CT: Information Age
Publishing.
Lazarus, R. S. (1991). Emotion and adaptation. New York: Oxford
University Press.
Lewis, L. K., & Seibold, D. R. (1993). Innovation modification
during intraorganizational adoption. Academy of Management Journal, 18,
322-354.
Manz, C. C., Bastien D. T., Hostager, T. J., & Shapiro, G. L.
(1989). Leadership and innovation: A longitudinal process view. In A. H.
Van de Ven, H. L. Angle, & M. S. Poole (Eds.), Research on the
management of innovation: The Minnesota studies (pp. 613-636). New York:
Harper & Row.
Mumford, M. D., Scott, G. M., Gaddis, B., & Strange, J. M.
(2002). Leading creative people: Orchestrating expertise and
relationships. Leadership Quarterly, 13, 705-750.
Oldham, G. R., & Cummings, A. (1996). Employee creativity:
Personal and contextual factors at work. Academy of Management Journal,
39, 607-634.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N.
P. (2003). Common method biases in behavioral research: A critical
review of the literature and recommended remedies. Journal of Applied
Psychology, 88, 879-903.
Quinn, R. E., & Cameron, K. S. (Eds.) (1988). Paradox and
transformation: Toward a theory of change in organizations and
management. Cambridge, MA: Ballinger.
Scott, S. G., & Bruce, R. A. (1998). Following the leader in
R&D: The joint effect of subordinate problem-solving style and
leader-member relations on innovative behavior. IEEE Transactions on
Engineering Management, 45, 3-10.
Sheremata, W. (2000). Centrifugal and centripetal forces in radical
new product development under time pressure. Academy of Management
Review, 25, 398-408.
Spector, P. E. (2006). Method variance in organizational research.
Truth or urban legend? Organizational Research Method, 9, 221-232.
Tierney, P., Farmer, S. M., & Graen, G. B. (1999). An
examination of leadership and employee creativity: The relevance of
traits and relationships. Personnel Psychology, 52, 591-618.
Tyler, T. R., Degoey, P., & Smith, H. (1996). Understanding why
the justice of group procedures matters: A test of the psychological
dynamics of the group-value model. Journal of Personality and Social
Psychology, 70, 913-930.
West, M. (2002). Sparkling fountains or stagnant ponds: An
integrative model of creativity and innovation implementation within
groups. Applied Psychology: An International Review, 51, 355-386.
Yukl, G. (2006). Leadership in organizations (6th ed.). Upper
Saddle River, NJ: Prentice Hall.
Authors' Note: We thank two anonymous reviewers for their
constructive feedback that helped to improve an earlier version of this
manuscript.
Diana E. Krause
University of Western Ontario, Canada
Diether Gebert
Korea National University, Seoul, South Korea
Eric Kearney
Technical University, Berlin, Germany
Diana E. Krause, PhD, is an assistant professor of organizational
behavior and human resource management at the University of Western
Ontario (Canada). Her research focuses on leadership, power, influence,
and trust in organizations; innovation and creativity; and assessment
centers.
Eric Kearney, PhD, is a researcher and lecturer at Technical
University of Berlin. His research interests include transformational
leadership, team innovativeness, diversity management, and attitude
change.
Diether Gebert is a professor of organizational behavior at the
Korea National University Business School, Seoul. His research includes
leadership, organizational change and organizational development,
philosophical aspects of organizations, diversity management, and team
performance.
Table 1
Advantages and Risks of Both Delegative-Participative and
Consultative-Advisory Leadership
Delegative-Participative Leadership Consultative-Advisory Leadership
Advantages Risks Advantages Risks
Increase in Frequent More discussions Increased
perceived mis- and about problems probability
situational reinter- inherent in the of reactance
control pretations implementation
Increased Increased Increased Increased
procedural relationship sense-making reluctance
fairnes conflicts to distribute
information
to others
Increased Increased Less ambiguity
intrinsic need for
motivation to coordination
implement
Increased Increased
implementation- acceptance of
related the innovation
personal
responsibility
Table 2
Means, Standard Deviations, and Correlations
Variable M SD 1 2 3 4
1. Job tenure 3.64 1.24 --
2. Degree of 4.78 1.31 -.01 --
innovation
3. Delegative- 5.20 1.64 -.05 .21 *** --
participative
leadership
4. Consultative- 4.13 1.51 .04 .11 * .32 *** --
advisory
leadership
5. Implementation 5.23 1.33 .07 .15 ** .49 *** .35 ***
success
Note: N = 388 managers. Pearson correlations.
Two-tailed significance tests.
* p < .05. ** p < .01. *** p < .001.
Table 3
Results of the Hierarchical Regression
Analysis of Implementation Success on
Delegative-Participative Leadership,
Consultative-Advisory Leadership,
and the Interaction of These
Leadership Patterns
Criterion
Implementation
Success
[beta]
Control variables
Job tenure .08
Degree of innovation .04
Predictors
Delegative-participative leadership .75 ***
Consultative-advisory leadership .70 ***
Interaction of both leadership patterns -.71 **
Values of the model
R .54
[R.sup. 2] ([R.sup. 2] adjusted) .30 (.29)
[DELTA] [R.sup. 2] for the interaction .03 ***
of both leadership patterns
F 39.14 ***
df1, df2 6,374
N 381
Note: N = 381 due to missing values in the variables.
[beta] = standardized regression coefficient.
R = multiple correlation coefficient. [R.sup.2] = explained variance.
** p < .01. *** p < .001.
COPYRIGHT 2007 Baker College System - Center for
Graduate Studies Reproduced with permission of the copyright holder. Further reproduction or distribution is prohibited without permission.
Copyright 2007, Gale Group. All rights
reserved. Gale Group is a Thomson Corporation Company.
NOTE: All illustrations and photos have been removed from this article.