Management Innovation and Organizational Performance: The Mediating Effect of Performance Management
Management Innovation and Organizational Performance: The Mediating Effect of Performance Management
JPART 21:367–386
Management Innovation and Organizational Performance: The Mediating Effect of Performance Management
Richard M. Walker*, Fariborz Damanpour�, Carlos A. Devece�
*University of Hong Kong; �Rutgers Business School; �Universitat Jaume
ABSTRACT
Management innovations (MIs) are widely adopted, but their influences on organizational
performance are little researched in public settings. Positing that the MI-performance
relationship is complex and is conditional over other characteristics of the organization, we
examine the influence of MI on organizational performance both directly and indirectly
through performance management (PM). PM is an important organizational process
characteristic arising from public management reform and in itself influences performance.
We test our hypotheses using structural equation models with data from three sources in
English local governments. The findings indicate that the impact of MI on performance is not
direct; it is mediated by PM. We also find that PM positively affects organizational
performance. In conclusion, we discuss the implications of these findings for research and
practice.
Innovations are adopted by public organizations to improve the services delivered to users
and citizens, with the broad aim of improving quality of life and building better and stronger
communities. Knowledge on the processes of innovation adoption and the characteristics of
innovative organizations is developing in public services settings (Boyne et al. 2005; Light
1998; Rashman and Radnor 2005; Walker 2006, 2008). Literature on whether adopted in-
novations are actually able to deliver positive outcomes is, by contrast, in its infancy. Find-
ings from qualitative and quantitative studies in the emerging literature are not unanimous
but often suggest a positive relationship (Light 1998; Moore 1995; Osborne 1998; Walker
and Damanpour 2008). However, similar to the studies of business organizations where the
focus has been on performance consequences of product innovations, the emphasis in pub-
lic organizations has been on the impact of service innovations.
In this article, we focus on management innovations (MIs) and examine its association
with organizational effectiveness or performance.We consider themechanisms throughwhich
MI could influence organizational performance in the public sector and examine whether its
influence on performance is mediated by performance management (PM)—a widely adopted
and promoted organizational process characteristic in the public sector. Our thesis stems from
a concern that direct-effects models exploring the innovation-performance hypothesis are over
Address correspondence to the author at rwalker@hku.hk.
doi:10.1093/jopart/muq043 Advance Access publication on August 18, 2010 ª The Author 2010. Published by Oxford University Press on behalf of the Journal of Public Administration Research and Theory, Inc. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
simple.We posit that the process of innovation adoption is complex, and there is mounting and
compelling evidence indicating that the impact of a management practice on performance is
dependent on other internal organizational characteristics (Birkinshaw andMol 2006; Jansen,
Van den Bosch, and Volberda 2006).
In our study, we seek to make a number of contributions. The first is to address the
imbalance within the innovation literature where influence of innovation on perfor-
mance has mainly been examined for product or technology-based innovations at
the industry or firm level (Adams, John, and Phelps 2006; Miles 2001). The second con-
tribution is to add to the growing body of evidence on the nature and influence of innovation
on performance in public organizations by developing and analyzing both a direct and a
mediated model of the innovation-performance relationship (O’Toole and Meier 1999).
The third is to examine the influence of MI on PM, a main pillar of public management
reforms in recent years (Boyne 2010; Heinrich 2002; Jennings and Haist 2004; Moynihan
2006). We explore these issues in English local government with data from three sources:
a survey, an audited external measure of organizational performance, and documentary
data from government departments and the census. We have tested our hypothesis by
using structural equation modeling (SEM), a rigorous analytical procedure for examining
mediating effects.
In the next section, we outline our hypotheses. This is followed by the study’s meth-
odology and statistical results. We conclude with a discussion of our findings and their
implications for future research and practice. We find no independent association between
innovation and performance; rather, we demonstrate that the impact of MI on performance
is mediated by PM. Figure 1 shows the study’s conceptual model.
THEORY
Reforms epitomized by the New Public Management (NPM) movement have led to major
changes in organization and management of the public sector based around the notion of
competitive markets and the adoption of private sector management practices. Public
organizations became engaged in restructuring their organization and improving manage-
ment processes in order to boost organizational performance. More recently, attention has
Figure 1 Conceptual Model
368 Journal of Public Administration Research and Theory
shifted to issues of governance and networking and the adoption of service improvement
strategies based around enhancing organizational and management capacities (Ingraham,
Joyce, and Donahue 2003; Moore 1995). We focus on two aspects of these public man-
agement reforms: introduction of MIs and PM. Though these are widely promoted, adop-
ted, and researched, evidence linking these activities with organizational outcomes is
remarkable by its scarcity (Boyne 2010; Walker 2010).
Adoption of MI
Innovation is generally defined as the generation (development) or adoption (use) of new
ideas, objects, or practices (Amabile 1988; O’Toole 1997; Rogers 1995). The generation of
innovation results in an outcome—a product, service, or practice that is new to the state of
the art (or at least to an organizational population); the adoption of innovation results in the
use of a product, service, or practice new to the unit of adoption—individual, team, or
organization (Damanpour and Wischnevsky 2006). This study focuses on the adoption
of innovation new to an organization.
Innovation adoption is a process that generally includes three phases: initiation, adop-
tion decision, and implementation (Damanpour and Schneider 2006; Rogers 1995). An
innovation is implemented when it is accepted by the users (employees, clients, or custom-
ers) and is regularly used by them. Therefore, for the innovation to deliver improvements
and contribute to organizational performance, it is necessary that it is implemented. This is
particularly important because public organizations may adopt an innovation in search of
legitimacy without fully implementing it (Ashworth, Boyne, and Delbridge 2009; Brown
and Potoski 2003; Feller 1981).
Innovation researchers have long distinguished among innovation types on the as-
sumption that they have different attributes and antecedents and follow certain adoption
processes (Daft 1978; Kimberly and Evanisko 1981; Light 1998). Whereas many typolo-
gies of innovation have been proposed (see Zaltman, Duncan, and Holbek 1973, 31), three
have been examined frequently: (1) product/service versus process innovations (Abernathy
and Utterback 1978; Walker and Damanpour 2008), (2) technological versus administra-
tive/managerial innovations (Damanpour, Walker, and Avellaneda 2009; Kimberly and
Evanisko 1981), and (3) radical versus incremental innovations (Cardinal 2001; Germain
1996). This study focuses on managerial innovation, one type of innovation whose con-
sequences have not been widely probed in the public context.
Birkinshaw, Hamel, and Mol (2008, 829) reviewed the literature on managerial in-
novation and defined it operationally as ‘‘the generation and implementation of a manage-
ment practice, process, structure, or technique that is new to the state of the art and is
intended to further organizational goals.’’ Examples include: divisional structure, Toyota
production system, total quality management (TQM), activity-based costing, modern as-
sembly line, and quality of work life (Birkinshaw, Hamel, and Mol 2008). As these exam-
ples suggest, MI is conceptualized as a multidimensional construct, including structural,
operational, and administrative processes. Further, because ‘‘newness’’ is defined as the
state of the art, these innovations are radical and their adoption may result in major changes
in the organization’s management systems and processes.
In this study, we use the definition of Birkinshaw et al. with two noteworthy mod-
ifications. First, as stated above, we focus only on the adoption, not the generation of in-
novation. Whereas an organization may both generate and then adopt and implement an
Walker et al. Management Innovation and Organizational Performance 369
innovation, it is also common that the innovation is generated by one organization and is
adopted by another.1 Second, we define ‘‘newness’’ relative to the adopting organization,
not the state of the art. This distinction is appropriate because we examine the influence of
MI related to NPM reforms on organizational performance. However, it affirms that MIs
examined in this study fall in the left side of innovation radicalness; that is, their adoption
may produce minor changes in the organization’s management systems and processes (see,
e.g., Damanpour and Schneider [2009, 516] for examples).
MIs, as compared with product/service innovations that are introduced for use by or to
serve external constituents, typically aim to increase efficiency and effectiveness of the
internal organizational operating and administrative processes (Adams, John, and Phelps
2006; Birkinshaw, Hamel, and Mol 2008; Boer and During 2001). They pertain to changes
in structure, management systems, knowledge used in performing the work of management,
and managerial skills that enable an organization to function efficiently and effectively
(Hamel 2006). Therefore, we conceive MI as a two-dimensional construct: an information
technology (IT) dimension and an administrative dimension. Whereas the administrative
dimension captures the adoption of new management systems and processes to make the
work of management more effective, the IT dimension reflects the use of new management
and office information systems to advance efficiency of the organization’s operating sys-
tems and processes (Damanpour, Walker, and Avellaneda 2009). Together, they represent
the introduction of new practices, processes, and techniques to further organizational
adaptation and effectiveness.
MI and Organizational Performance
Only limited empirical attention has been focused upon the innovation-performance hy-
pothesis in public agencies (Damanpour, Walker, and Avellaneda 2009; Salge and Vera
2009; Walker and Damanpour 2008). Whereas extant work does not examine performance
consequences of MIs in particular, it provides evidence to support the notion that innova-
tion may unfold and influence organizational performance in different ways—findings that
corroborateWalker’s (2004) quantitative review of studies across public and private sectors
that innovation influences performance positively. The balance of evidence suggests that
although innovation is risky and its success is not guaranteed, its adoption enhances per-
formance. It confirms views espoused by contingency and resource dependence theories
that organizations are adaptive systems that introduce change in order to function effec-
tively (Lawrence and Lorsch 1967; Pfeffer and Salancik 2003).
MI can play a central role in the process of changing organizations, facilitating or-
ganizational adaptation to the external environment and increasing the efficiency and ef-
fectiveness of internal processes. For instance, the adoption of MIs such as the balanced
score card and TQM in public agencies seek to increase organizational performance, align-
ing the organization with the environmental demands of quality public services at lower
costs. The critical review of Boyne and Walker (2002) indicates that TQM has positive
performance consequences, but the evidence was not equivocal. Argument from institu-
tional theory has alternatively suggested that MI may have indirect performance impacts
1 For more detail description of generation and adoption process and differences between the characteristics of
innovation-generating and innovation-adopting organizations, see Damanpour and Wischnevsky (2006).
370 Journal of Public Administration Research and Theory
because factors driving adoption are initially focused upon securing internal and external
legitimacy (Staw and Epstein 2000). Although large sample empirical studies of the re-
lationship betweenMI and organizational performance are scarce, evidence from case stud-
ies repeatedly points toward the positive effects of the adoption of MIs (Birkinshaw and
Mol 2006; Hamel 2006). For instance, Hamel (2006) cites cases from the private sector in
the early 1900s such as Mary Parker Follett’s experiences of building and running com-
munity-based organizations in Boston to more modern-day MIs in nonprofit ventures such
as Bangladesh’s Grameen Bank. We therefore hypothesize,
H1 Management innovation is positively associated with organizational performance.
MI and PM
At the heart of public management reforms have been attempts to deal with some of the
major maladies of public organizations, such as goal ambiguity, red tape, low productivity,
and bureaucratic imperialism (Rainey 2003; Wilson 1989). A central reform strategy has
been to promote PM (OECD 2005; Pollitt and Bouckaert 2004) also referred to as ‘‘man-
aging for results’’ (Moynihan 2006) and ‘‘managing for outcomes’’ (Heinrich 2002). PM is
associated with setting clear organizational goals, specifying targets and indicators to link
goals to performance outcomes, and taking action to influence achievement against targets
(Boyne 2010; Jennings and Haist 2004; Rainey and Rhu 2004). To facilitate buy-in of mis-
sions and goals and to assist with meeting targets, PM regimes seek to empower middle
managers to make decisions and take responsibility of their unit’s conduct and outcomes.
Simultaneously, senior executives have been mandated to intervene, make corrective ac-
tions in a coordinated manner, and adapt strategy when necessary (OPSR 2002;Walker and
Boyne 2006).
MIs can further these organizational processes by introducing practices new to the
organization. The desired, intended consequence of both MI and PM is organizational ef-
fectiveness. Therefore, innovations that assist public agencies in meeting their objectives
are more likely to succeed where there is an affinity between existing goals, targets and
indicators and the new practices being implemented. Over the long-term innovations may
change the goals of organizations; for example, new information technologies such as Geo-
graphical Information Systems may lead to new data on client needs that could result in
targeting new client groups, thus achieving important equity outcomes necessitating new
targets and indicators. Innovations that are more closely tied to organizational missions and
strategies will more likely help reinforce the implementation of organizational processes
associated with PM.
The component elements of MI—operational and administrative—can play important
roles in bridging the challenges of managing top-down and bottom-up processes. The ad-
ministrative component can play a fundamental role, especially in planning and budgeting
because the management control system (comprising of the budgeting system and incentive
system) should ‘‘. . .motivate managers to make the same decisions senior managers would have made in the circumstances’’ (Teall 1992, 32). The operational component, which
in service organizations is mainly based on changes in information technologies and
systems—where there has been substantial improvements in public organizations
(Reschenthaler and Thompson 1996)—is also relevant in the success of PM. Information
systems facilitate the link between the corporate structure and other parts of the
Walker et al. Management Innovation and Organizational Performance 371
organization through collection, process, and dissemination of data on performance indi-
cators. Together, MI components facilitate organizational units’ capability to introduce
measures of performance consistent with overall organizational goals, thereby work in tan-
dem to implement the overall PM system (Teall 1992). Therefore,
H2 Management innovation is positively associated with performance management.
PM and Organizational Performance
PM sits within a tradition of rational approaches to management in the public sector (see
Boyne [2010] for a review), of which the primary purpose is to ‘‘improve public manage-
ment and program outcomes’’ (Heinrich 2002, 712). One area PM seeks to tackle is the
ambiguous nature of organizational goals which can arise from the complex, multiple, and
conflicting nature of many public agencies’ goals—contrast garbage collection with polic-
ing or health care (Rainey 2003). Many public organizations are staffed by diverse groups
of professionals who may have very different views about appropriate organizational ob-
jectives and have inadequate cross-functional management skills. These conflicts of goals
and personnel can complicate coordination of activities of individuals and teams and in-
tegration of organizational units, harming organizational efficiency and effectiveness
(Chun and Rainey 2005). Given these characteristics and findings, a number of studies
highlight the importance of focus and clarity around the organizational mission and
goals as a critical characteristic of higher performance (Rainey and Rhu 2004; Rainey
and Steinbauer 1999; Weiss and Piderit 1999).
Target setting and PM is one of the key mechanisms by which the difficulty of goal
ambiguity can be tackled—put simply goals are linked to outcomes. An additional purpose
of target setting is to combat bureaucratic imperialism and ensure the information asym-
metries between bureaucrats and other stakeholders are broken down. PM systems are
needed because public organizations cannot plan for performance improvements if they
are not aware of the starting point and do not have information for manager’s to measure
progress toward targets. These approaches reflect models of strategic planning that specifies
clear targets, detailed plans, and the close monitoring of the targets. Empirical evidence
increasingly points to the likely success of strategic planning, target setting, and PM in
improving public service performance (Boyne and Chen 2007; Hendrick 2003; Hyndman
and Eden 2001; Walker and Boyne 2006).
Appropriate structures for achieving delegation and control, and for ensuring that
goals are implemented and targets are achieved, are essential for organizational effective-
ness. On one hand, successful implementation of goals and targets requires top managers to
intervene and change organizational direction when problems occur. Timely corrective
action by top executives is one strategy to reduce the likely detrimental effects of internal
conflict by offering clear lines of hierarchal authority. Such actions are among responsi-
bilities of organizational leaders and do not necessarily reflect a centralized, vertical de-
cision making structure. On the other hand, devolved decision making and ensuring that
decisions are made as close to the users and citizens as possible increase line managers’
capacity to meet targets and give them needed flexibility to respond to changing environ-
mental circumstances. The empirical evidence on the relative merits of top management
intervention and devolved management is limited and mixed in public organizations
(Andrews et al. 2009). Given effective organizations require control, delegation, and
372 Journal of Public Administration Research and Theory
cooperation, we, therefore, propose both top managements’ corrective actions and de-
volved management will positively affect organizational performance. Thus,
H3 Performance management is positively associated with organizational performance.
METHODS
Sample and Data
We examined English local governments or authorities. Local authorities are elected bod-
ies, operate in specific geographical areas, employ professional career staff, and receive
approximately two-thirds of their income from the central government. They are multipur-
pose organizations and deliver services including education, social care, land-use planning,
waste management, housing, leisure and culture, and welfare benefits. In urban areas, uni-
tary authorities deliver all these services; in predominately rural areas, a two-tier system
prevails with county councils administering education and social services and district coun-
cils providing welfare and regulatory services. In this study, we do not include district
councils because our dependent variable (organizational performance) is only available
for the unitary and upper-tier authorities.
The data come frommultiple sources. For the dependent variable, the data are taken from
a data set created by the Audit Commission (2002) (details below). The Commission acts on
behalf of central government, provides audit, inspection services, and value-for-money
investigations and is therefore an important external stakeholder for local governments.
For control variables, the data come from UK census (details below). Data for the measures
of MI and PM are from a survey of English local government. Our data have a lagged
structure: the measure of organizational performance was recorded in 2005 and the
measures of MI and PM in 2004, and control variables are from 2004 and earlier.
The survey was administered to a census of the 139 unitary and upper tier authorities
and responses were received from 136 authorities—a response rate of 98%. The survey was
pretested in 17 local authorities (and 378 respondents) and conducted electronically
(Enticott 2003). Questionnaires were delivered as Excel files attached to e-mail and were,
therefore, self-coding. Informants had 8 weeks to return the file by e-mail, and during this
period, three reminders were sent to informants who had not responded. There were no
statistically significant differences between late and early respondents.
The survey was a multiple informant survey. Multiple informant surveys aim to cap-
ture internal organizational variety in a compatible format (Phillips 1981) collecting data
from informants from several managerial levels or ‘‘echelons.’’ Aiken and Hage (1968,
918) define an echelon, or social position in an organization, as ‘‘the level of stratum
in the organization, the department or type of professional activity.’’ Hence, in each local
authority, questionnaires were sent to two echelons—three corporate officers and four of-
ficers in each of the seven service areas mentioned above.2 All survey questions were in the
form of a seven-point Likert scale and informants were asked to rate their authority (for
corporate officers) or service area (for service area officers). A total of 1,056 informants
2 Corporate officers include the chief executive officer and corporate policy officers with cross-organizational
responsibilities for service delivery and improvement. Service officers include chief officers who are the most senior
officer with specific service delivery responsibility and service managers or frontline supervisory officers.
Walker et al. Management Innovation and Organizational Performance 373
responded to the survey of which 196 were corporate officers and 860 service officers
(48.4% and 22.7% response rates, respectively). To calculate an organizational mean,
we first calculated a mean of corporate officers and a mean of service officers giving equal
weight to each tier; the organizational score is then derived from these two means (Aiken
and Hage (1968). This procedure maintains variations across organizations and converts
categorical data to continuous data. Furthermore, data from two tiers help overcome the
sample bias problem faced in surveying informants from one organizational level only
(Bowman and Ambrosini 1997).
Measures
Organizational performance (OP) was measured by the core service performance (CSP)
score constructed by the Audit Commission (2002). For each of the seven service areas, the
CSP score is based largely on archival performance indicators, supplemented by the results
of inspection and assessment of statuary plans (Andrews et al. 2005). The archival perfor-
mance indicators cover six aspects of organizational performance: quantity of outputs (e.g.,
number of home helps for the elderly), quality of outputs (e.g., number of serious injury on
highways), efficiency (e.g., cost per benefit claimed), formal effectiveness (e.g., average
school passes at 16), equity (e.g., equal access to public housing), and consumer satisfaction
(e.g., satisfaction with waste collection). Inspection of services draws upon internal im-
provement plans, field visits, and other documentation. Statutory plans are assessed against
the criteria of the service’s relevant central government department. Evaluators external to
the local authority conduct all assessments. Each service area is given a performance score
by the Audit Commission from 1 (lowest) to 4 (highest).
After calculating the CSP score for each service area the Audit Commission derives
a score for the whole organization by weighting services to reflect their relative importance
by budget (the weight for education and social services is 4, for environment health and
housing is 2, and for libraries and leisure, benefits, and management of resources is 1). The
Commission then combines these weights with the performance score (1 – 4) for each ser-
vice area to calculate the CSP. The resulting scores range from a minimum of 15 (12 in the
case of county councils that do not provide either housing or benefits) to a maximum of 60
(48 for county councils). To make the CSP scores comparable across all authorities, we
calculated the percentage of the maximum possible CSP score for the given local govern-
ment. Therefore, the measure of organizational performance in this study is an aggregate
measure across the key services areas of local governments and includes multiple indicators
of performance for each service area.
MI was measured by five survey items that explore employees’ perception of the in-
troduction of new management practices and techniques (Appendix lists scales and ques-
tions). The IT innovation dimension includes new techniques primarily aimed at modifying
the organization’s operating processes and systems (MI1 andMI2), whereas administrative
innovation dimension includes new practices mainly seeking to alter the organization’s
administrative processes and systems (MI3, MI4, and MI5).
PM as defined earlier has several components. First, it ensures that organizational
mission and operational goals are specified, understood, and accepted across the organi-
zation (PM1, see Appendix). Second, the specification of performance targets and measures
ensures the strategy, and how it is implemented tactically and operationally, is continually
assessed (PM2). Third, the clear specification of objectives and their understanding across
374 Journal of Public Administration Research and Theory
the service areas permits devolution of control to line managers who can make local de-
cisions based on the wider organizational mission and goals (PM3). Fourth, serious devia-
tions from the plans that surpass the local scope and resources are communicated to top
management and the corrective action is applied in the organization (PM4).3
External constraints may cloud the relationship between MI, PM, and organizational
performance. Researchers have controlled for a variety of contextual factors (Andrews et al.
2005; Boyne et al. 2005; O’Toole andMeier 2003; Pettigrew, Ferlie, andMcKee 1992).We
tested the influence of seven factors that were used in the other studies from this data set on
organizational performance: service need, diversity of need (by age, ethnic, and social
class), slack resources, population density, and change in population (Andrews et al.
2005) and prior performance (O’Toole and Meier 1999; Staw and Epstein 2000).4 The
definitions, measures, descriptive statistics, and correlations of control variables are avail-
able from the authors.
Table 1 provides descriptive statistics and correlations for MI, PM, and organizational
performance.
Analysis
We used two analytical methods. First, to test the mediation effect of PM in the relationship
between MI and organizational performance, we used SEM. The software employed was
EQS 6.1. The maximum likelihood method, combined with the method of robust standard
estimators, was used to overcome restrictions due to the nonnormality of the data (Satorra
and Bentler 2001). The overall fit of the models was evaluated by a combination of ab-
solute, incremental, and parsimonious fit indexes recommended by Hair et al. (1992)
and Jöreskog and Sorbom (1993). Before the hypothesized model was estimated, the mea-
surement scales of multi-indicators MI and PM were assessed by conducting confirmatory
factor analysis (CFA) (Bagozzi 1981). OP was a single indicator and was thus assumed not
to contain measurement errors. The conceptual model (figure 1) consists of one exogenous
variable (MI) and two endogenous variables (PM and OP). Second, we conducted hierar-
chical regression analyses to ensure that the influence of MI and PM on performance is
beyond and above that of control variables.
Table 1 Means, SDs, and Correlations
Mean SD Minimum Maximum Correlations
(1) MI (.80) 5.12 0.54 3.50 6.66 1
(2) PM (.73) 5.26 0.45 3.34 6.30 .38** 1
(3) OP 68.02 8.79 40.0 90.00 .04 .35**
Note: Reliability coefficients (Cronbach’s alpha) for the scales are in parenthesis; n 5 136. **p , .01 (two tailed).
3 To test if MI and PM are different constructs, we ran an EFA. Analysis clearly isolated two factors that correspond
to MI (eigenvalue 1.618, minimum correlation .595) and PM (eigenvalue 3.502, minimum correlation .665).
4 Prior performance was included because (1) performance of most organizations, especially public organizations,
alter incrementally through time (O’Toole and Meier 1999); and (2) inclusion of an autoregressive term helps
controlling for unspecified correlates of performance, ensuring that coefficients for MI and PM are not biased
(Pedhazur 1982).
Walker et al. Management Innovation and Organizational Performance 375
RESULTS
Measurement Models
The MI
As stated above, the MI construct was conceptualized and measured as a two-dimensional
factor. The reliability and convergent validity of MI measurement model were assessed by
a CFA. Because of the saturation of the second-order measurement model, the validation of
the scale was conducted in a first-order model with a covariance between the dimensions.
The goodness-of-fit indexes of the five-item MI scale with two dimensions are provided in
Appendix. The incremental fit indexes (comparative fit index [CFI] 5 .94, incremental fit index [IFI] 5 .94) exceeded the recommended minimum value of 0.90 (Hair et al. 1992), although the nonnormed fit index (NNFI) was low (.85). Nevertheless, the values of the rest
of the indexes together with a high NFI (.92, not shown in Appendix) assures the good fit of
the data. The absolute fit index root mean square error of approximation (RMSEA) (5.116) was slightly high, but the parsimonious normed chi-square (NC) index (52.80) was lower than the maximum value of 3.0 (Kline 1998). Besides, the Cronbach’s alpha was .80 and all
the loadings were greater than 0.60, surpassing the minimum value recommended of 0.50
(Hair et al. 1992). The convergent validity of the scale was examined by the composite
reliability of the construct (Werts, Linn, and Jorekog 1974), reaching a value of 0.80. These
tests guarantee that the MI scale fulfills the psychometric properties necessary in measure-
ment scales (Hair et al. 1992).
The PM
To check the unidimensionality of the PM construct, we conducted an exploratory factor
analysis (EFA). A single dimension was extracted, with the lowest loading item (PM4)
higher than 0.62. The CFA showed that all the indices have adequate fit (NNFI 5 .98; CFI 5 .99, IFI 5 .99; NC 5 1.7; RMSEA 5 .035) and Cronbach’s alpha (.734) is satis- factory (Appendix). The standardized loadings from the CFA for all items were higher than
0.50, with the exception of PM4 (0.45). This low loading is also reflected in the composite
reliability of the scale (0.59), pointing out the limited number of items employed in the
measurement of a multidimensional and conceptually complex construct such as PM. How-
ever, the robustness of the rest of indexes guarantees the validity of the scale.
Structural Model
We tested the hypotheses jointly by the structural model (Model 1, figure 2). Applying the
maximum likelihood method, all the indices indicated that the hypothesized model had
adequate fit to the data (NNFI 5 .93; CFI 5 .95, IFI 5 .95; NC 5 1.38; RMSEA 5 .054). Figure 2 also contains the parameter estimates for the main predictors, significance
levels, and proportions of explained variance (R2).
Hypothesis 1 was not supported as the path coefficient between MI and organizational
performance is not significant (2.22, p. .05).5 However, the path coefficient between MI
5 The direct effect of MI on performance is significant at the .10 level, however. This negative effect, after
discounting the positive effect mediated by PM, may arise because of the possible disruptive impact of innovation and
short-term (1 year) lag in our model. Longitudinal data are needed to confirm.
376 Journal of Public Administration Research and Theory
and PM is positive (.52, p, .01), supporting Hypothesis 2. MI explains 27% of variance in PM. Hypothesis 3 was also supported as the path coefficient between PM and organiza-
tional performance is positive and significant (.52, p , .01).
Additional Analysis
Alternative SEM Model Evaluation
The hypothesized model (Model 1) is a partially mediated model since the effect of MI
on organizational performance is considered both directly and indirectly through PM. To
shed more light on the MI-performance relationship, we conducted additional SEM
analyses to test the validity of nonmediated and fully mediated models (figure 3). Model
2 is a nonmediated model and assesses the independent effects of MI and PM on perfor-
mance; Model 3 is a fully mediated model and has the same number of paths as Model 2.
These models allow the comparison of direct and indirect effects of MI on performance.
Since Models 1–3 are nested models, we compared the fit of the hypothesized model
(Model 1) and the alternative models (Models 2 and 3) by the significance of change
in chi squared.
In Model 2, the data did not fit adequately (NNFI5 .72; CFI5 .75, IFI5 .81; NC5 2.35; RMSEA5 .101), delineating that hypothesized model is superior to the nonmediated model. In Model 3, the data fit well (NNFI 5 .92; CFI 5 .94; IFI 5 .95; NC 5 1.43; RMSEA 5 .057) and the chi-square was greater than that in Model 1 (x2 5 42.76 versus 45.89); however, the difference between the chi-squares was not significant (Dx2 [1] 5 3.13, p . .05). Because Model 3 is more parsimonious than Model 1 and the difference in chi-square is not statistically significant, this alternative model is considered better than
the hypothesized model. Thus, the data indicate that the path between MI and performance
in Model 1 does not represent any improvement in explaining performance; that is, MI
affects organizational performance mainly through PM.
Figure 2 Path Coefficients for the Hypothesized Model
Walker et al. Management Innovation and Organizational Performance 377
Stepwise Regression Analysis
Whereas SEM is the most suitable model for analyzing the mediating effects as it allows
inclusion of both observed and unobserved (latent) variables in MI and PM constructs, it
restricts the number of parameter (variables) that can be included per a certain sample size
and the addition of nonsignificant control variables usually deteriorates the fit of the model
(Kline 1998). Therefore, we tested the influence of the control variables first by regressing
organizational performance on each of the seven control variables alone. None of the re-
gression models or regression coefficients was statistically significant (p. .05). Then, we conducted a multiple regression analysis regressing performance on all controls and
prior performance (organizational performance in year 2004). With exception of the
coefficient for prior performance (p , .001), none of the regression coefficients was sig- nificant (p . .05). Therefore, we only considered prior performance for the stepwise regression analysis.6
Figure 3 Alternative SEM Models
6 The regression models with the control variables are available from the authors.
378 Journal of Public Administration Research and Theory
We examined three models (Models 1–3, Table 2), entering MI, PM, and prior orga-
nizational performance (measured by 2004 CSP score) as explanatory variables, respec-
tively.7 Model 1 was not significant (F 5 .14, p . .05), but Models 2 and 3 were (p , .001). Further, the regression coefficient in Models 1 was not statistically significant (p. .05). In Model 2, only the coefficient for PM was significant (.39, p, .001). In Model 3, only the coefficients for PM and prior organizational performance were significant (.20,
p, .01 and .54, p, .001, respectively).8 These results confirm the findings from the SEM analysis (Model 1), delineating that PM, but not MI, affect organizational performance.
DISCUSSION
In this study, we have examined independent and joint effects of MI and PM on organi-
zational performance. We conducted statistical tests using structural equation models in
a sample of English local governments. The main findings from this study are that (1)
MI does not have a direct impact on organizational performance, (2) PM directly affects
organizational performance, and (3) the effect of MI on organizational performance is fully
mediated by PM.
The literature on innovation and performance in the public and private sectors led us to
hypothesize that there would be a positive relationship between MI and organizational per-
formance. Our analysis, however, indicates that PM mediates this relationship (Model 3,
figure 3). Although the balance of evidence on the direct effect of innovation on perfor-
mance is weighted toward positive findings, previous research has not examined the pos-
sible mediating effects of other variables. Therefore, our study’s findings signal the need for
more extensive research on the innovation-performance relationship counting for the me-
diating role of organizational attributes and processes.
Indeed, there are spots of evidence in previous research that raises the possibility
of the so-called ‘‘pro-innovation bias’’ (Rogers 1995). First, as stated above, the patterns
of adoption, antecedents, and consequences of different types of innovation are not nec-
essarily the same. Further, the bulk of knowledge on adoption comes from the private sector
Table 2 Stepwise Regression Resultsa
Model 1 Model 2 Model 3
MI .03 2.11 2.03 PM .39*** .20*
Prior organizational performance (year 2004) .54***
F .14 9.66* 27.63*
Adjusted R2 2.01 .12* .38* Change in R2 .13* .26* aThe dependant variable is organizational performance (year 2005). Table entries are standardized regression coefficients.
*p , .05, **p , .01, ***p , .001.
7 To test for the mediation effect, we also implemented the approach suggested by Baron and Kenny (1986). The
results did not shed any further light on the conceptual model (they are available from the authors). Thus, in keeping
with recommendations from Judd and Kenny (1981), we present the final stages of the stepwise regression.
8 We also tested nonlinear effect of PM on performance (i.e., testing whether too much emphasis on PM could be
detrimental to performance). The coefficient of the quadratic term of PMwas nonsignificant (p. .05), and other results remained unchanged.
Walker et al. Management Innovation and Organizational Performance 379
and manufacturing in particular. These studies have predominately focused on technology-
based product and process innovations and have examined means of appropriating benefits
that determine the technological trajectory, leading to a focus on ‘‘product or technology life
cycle’’ models and discontinuous radical technological change (Abernathy and
Utterback1978;AndersonandTushman1991).These technology-drivenmodelsareperhaps
not suited to an understanding of the adoption of innovations in public service organizations,
especiallyMIs. This and other studies (Borins 1998;Moore andHartley 2008;Walker 2008)
are making progress in deciphering evidence on innovation types in public organizations.
For example, Moore and Hartley (2008) argue that innovation types are more blurred and
dimensional in the public sector, and rather than following a linear trajectory, public
agencies may simultaneously adopt innovations, making the successful adoption of one in-
novation dependent upon another. However, this research stream is still in its infancy. More
workneeds to beundertaken for understanding the adoption of different innovation types and
their distinct impact on organizational performance in public organizationswhichmay in the
future offer alternative interpretations of the adoption and impact of MI than those offered
here.
Second, large-sample empirical studies of the influence of MI on organizational
performance are scarce. Evidence has come mainly from case studies (Gold 1982;
Hamel 2006; Light 1998). Our probing of the MI, PM, and performance relationship
supports the case study contention that MI is a force for good; however, it adds that
the relationship between MI and performance is subject to the focal organization’s ability
to have in place management systems and effectively manage organizational processes to
implement its mission and strategies. Hamel (2006, 75–6) associatesMI with ‘‘. . . changing how managers do what they do.’’ In order to ‘‘change how managers do what they do’’
and for the adoption of MI to enhance performance, mechanisms to ensure that the
adopted innovation is successfully implemented are necessary. Our research findings
suggest that PM brings a degree of congruence between MI and performance. For public
services managers, this finding implies that for gaining the greatest rewards from the in-
troduction of MI, they need to ensure that appropriate PM frameworks are in place because
without them the likely performance gains fromMIwill not materialize. Given that we have
only examined one set of organizational processes, future innovation research should
investigate the role of other key processes (e.g., strategy formulation and content,
leadership, communication, and conflict resolution) as mediators or moderators of MI
and performance.
Third, as explained above, as process innovations, antecedents, and consequences of
MIs are often contrasted with product/service innovations. For instance, ‘‘performance-
gap’’ and ‘‘first or early mover advantage’’ perspectives suggest that product/service inno-
vations have a more direct effect on organizational outcomes than process/MIs (Roberts
and Amit 2003; Wischnevsky and Damanpour 2006). According to these perspectives,
changes in management systems and processes may affect the organization as a whole
and could have consequences for organizational outcomes; however, their effect is more
indirect and takes more time to occur than changes in products or services. In public service
organizations, for example, the introduction of new services to assist elderly people to re-
main in their homes rather than move into residential or hospital care is likely to see a very
immediate and positive effect on effectiveness of these services to this constituency. By
contrast, the adoption of a new budgeting system may take a number of years to impact on
380 Journal of Public Administration Research and Theory
the allocation of resources and may need other mechanisms to ensure that new budgeting
processes are embedded into the organization. Therefore, one interpretation of our findings
is that the negative affect of MI on performance (albeit at the .10 significance level) is
a result of the short time lag (one year) in our study. Additional research using longitudinal
data is required to compare and contrast performance consequences of MIs in different
public services and examine in greater detail the time lags between the adoption of
MIs and their impacts on performance.
Finally, we are able to conclude that the emphasis on organizational processes in pub-
lic management reforms could play an important role in public agencies. There has been
skepticism surrounding the adoption of many management reforms that have sought to
tackle the maladies of vague goals or high levels of red tape (see, e.g., Fountain 2001).
Our findings challenge these a
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