npd planning activities and innovation performance: the mediating role of process management and the...

NPD Planning Activities and Innovation Performance:

The Mediating Role of Process Management and

the Moderating Effect of Product Innovativeness

Soren Salomo, Joachim Weise, and Hans Georg Gemunden

The aim of this study is to investigate the effects of planning and control on the

performance of new product development (NPD) projects. It is hypothesized that

(1) thorough business planning at the beginning of a project creates a basis for

proficient project and risk planning; (2) the proficiency of project planning, risk

planning, and process management activities each improves innovation performance

directly; (3) the relationship of planning and success is mediated by process man-

agement; and (4) the strength of these relationships is moderated by uncertainty, as

determined by the degree of innovativeness. To test the hypotheses, data from 132

NPD projects were collected and analyzed. A measurement model was used to es-

tablish valid and reliable constructs, a path model to test the main effects, and a

multiple-moderated regression analysis for the moderator hypotheses. The results

suggest that the proficiency of project planning and process management is impor-

tant predictors of NPD performance. Specifically, project risk planning and goal

stability throughout the development process are found to enhance performance

significantly. Business planning proves to be an important antecedent of the more

development-related planning activities such as project planning and risk planning.

Additionally, the results lend support to the hypotheses regarding the mediating role

of process management in the planning–performance relationship. Project planning

and risk planning support the quality of process management and thus impact NPD

performance indirectly. Only to a limited extent are the strengths of these rela-

tionships moderated by the degree of innovativeness of the NPD project.

Introduction

Innovative new products play an important role

in building competitive advantage and can con-

tribute significantly to a firm’s growth and prof-

itability. Although product innovation is widely

recognized as a potentially vital source of competitive

advantage, firms still struggle to find efficient and ef-

fective processes and management activities for new

product development (NPD). Product development

appears to be especially difficult if firms have limited

experience with the product or the process technolo-

gies used to develop it (Tatikonda and Rosenthal,

2000). The need to engage in product innovation,

however, has become increasingly important as com-

panies face the threat of significant decline if they are

not able to keep pace with disruptive changes in their

industries—changes often related to radical techno-

logical developments (Christensen and Overdorf,

2000; Clark and Fujimoto, 1991; Pfeiffer, 1985; Tush-

man and O’Reilly, 1996). To date, it is not clear if the

best practices associated with developing continuous

Address correspondence to: Soren Salomo, Karl-Franzens Univer-sity Graz, Universitatsstr, 15/G3, 8010 Graz, Austria. E-mail: [email protected].

J PROD INNOV MANAG 2007;24:285–302r 2007 Product Development & Management Association

products also apply to discontinuous products. NPD

projects that feature a high degree of innovativeness

may require a different management approach than

that used for incremental or moderate innovations

(Salomo, 2003; Song and Montoya-Weiss, 1998). And

some of the established practices in incremental NPD

may actually be counterproductive in the context of

highly innovative, discontinuous development pro-

jects (Leifer et al., 2000; Veryzer, 1998).

This article focuses on planning and process con-

trol activities as central practices of NPD. Tradition-

ally, the rational plan approach to NPD (Brown and

Eisenhardt, 1995) presumes that development activi-

ties are relatively predictable and are best managed as

a top-down process whereby monitoring, evaluation,

and control activities appear tightly coupled in a sys-

tematic cycle. Milestones help a team to track a pro-

ject methodically; formal reviews enable critical

assessments that inform major decisions; and direc-

tive control allows managers to adjust project resourc-

es and objectives as necessary (Rosenau and Moran,

1993; Wheelwright and Clark, 1992). Although it is

generally acknowledged that a certain degree of free-

dom and flexibility are essential ingredients for the

success of product development teams (Burns and

Stalker, 1961; Moorman and Miner, 1998), tradition-

al formal controls at the project level continue to be

one of management’s main tools for keeping NPD

projects on schedule, within budget, and aligned with

strategic goals (Cooper and Kleinschmidt, 1995). The

critical question in the context of radically new prod-

ucts is the amount of control that should be exercised

to keep the project on track while avoiding dysfunc-

tional effects (Brown and Eisenhardt, 1997).

Although project characteristics are known to

make a difference (Shenhar, 2001; Song and Mon-

toya-Weiss, 1998), to date few empirical studies have

systematically investigated the extent to which the ef-

fect of planning and control activities is contingent

upon a product’s degree of innovativeness. In viewing

the available evidence, it is often difficult to find a

common denominator, and in some cases the findings

are entirely contradictory. Although the study of She-

nhar et al. (2002), for example, reveals that detailed

project planning is especially important for complex

projects involving high uncertainty, Song & Montoya-

Weiss (1998) found that project planning can be coun-

terproductive for highly innovative projects. Similarly,

whereas Tatikonda and Montoya-Weiss (2001) state

that process formality has a positive impact on project

operational outcomes irrespective of the technical un-

certainty faced by the product, Lewis et al. (2002) iden-

tified a negative interaction between planned style

project management and technical uncertainty, and

Griffin (1997) found no significant relationship between

process formality and development time. Although

these and other research studies present valuable in-

sights into the effect of planning and process structur-

ing on NPD performance, the present article intends to

contribute to this literature in three main ways.

First, it investigates the moderating role of product

innovativeness in the relationship between various plan-

ning and control activities and new product success.

Based on recently suggested measurement concepts,

product innovativeness is best understood and measured

as a multidimensional phenomenon (Danneels and

Kleinschmidt, 2001; Gatignon et al., 2002; Salomo,

2003). In addition, specific care was taken to include

projects with widely differing degrees of innovativeness in

the study’s sample to assist in detectingmoderator effects.

BIOGRAPHICAL SKETCHES

Dr. Soren Salomo is professor of technology and innovation man-

agement at Karl-Franzens University Graz in Austria. He holds a

diploma and a doctorate in business administration from Kiel Uni-

versity and a habilitation degree from Berlin University of Tech-

nology. He received the Esche-Schumann-Commichau Foundation

award for his doctoral thesis. His research interests cover corporate

innovation management from a resource-based perspective with a

special focus on process and organizational system mechanisms for

supporting radical innovation. He also addresses research questions

in the field of innovation marketing. His work is published in Scan-

dinavian Journal of Management, Creativity and Innovation Man-

agement, and other noted refereed journals.

Dr. Joachim Weise is a project leader with The Boston Consulting

Group, a leading international strategy consulting firm. He has ad-

vised clients in a broad range of industries, including telecommu-

nications and industrial goods, on strategy issues, product

innovation management, and profit improvement. Dr. Weise holds

a Ph.D. and a diploma in industrial engineering from the Technical

University of Berlin and an M.Sc. in production management from

the Chalmers University of Technology in Goteborg. His research

interests include innovation management, product development,

and technology management and forecasting in high-technology

environments.

Dr. Hans Georg Gemunden is professor of technology and inno-

vation management at the Berlin University of Technology. He

holds a diploma and a doctorate in business administration from

Saarbucken University and a habilitation degree from the Univer-

sity of Kiel. He has published several books and numerous articles

in the fields of innovation and technology management, marketing,

business policy and strategy, project management, entrepreneur-

ship, human information behavior and decision making, and ac-

counting. He has received several Awards of Excellence for his

research, which is published in refereed journals including R&D

Management, Research Policy, International Journal of Research

in Marketing, Journal of Costumer Behaviour, and Organization

Science.

286 J PROD INNOV MANAG2007;24:285–302

S. SALOMO, J. WEISE, AND H.G. GEMUNDEN

Second, the study acknowledges that, from an in-

formation processing point of view, both information

generation and processing are vital for NPD success.

Employing a path model, the study explicitly exam-

ines how the quality of project execution mediates

the relationship between project planning and

NPD success. The approach contrasts with that of

previous NPD research that has primarily focused on

planning or process factors without considering their

interaction.

Third, the present study contributes to the extant

literature by employing more detailed operation-

alizations, incorporating multiple dimensions for

each of the major constructs. Although broad con-

structs foster generalizability, this study concurs with

Dougherty (1996) that a stronger focus on the actual

activities of product innovation allows a more thor-

ough treatment of the particular processes and is like-

ly to produce greater stability in the proposed

relationships.

In the following sections are presented the concep-

tual foundations for the study’s model of planning

and control of NPD projects and the hypotheses

about the expected moderating effects of the degree

of innovativeness. Then a description is given of the

research methods and report tests of the study’s model

using project-level data on 132 recently launched new

products. The article concludes with a discussion of

the implications of the study’s findings and sugges-

tions for avenues for future research.

Contingency Model of Planning and Process

Management Effectiveness

Model Overview

This article intends to analyze the performance effects

of different planning and process management activ-

ities in NPD projects. Apart from investigating the

direct effects of each of these activities, the study also

hypothesizes that planning activities have an impact

on process management activities, a link that has, to

date, been confined primarily to the general project

management literature outside the context of NPD

projects (Lechler, 1997; Pinto and Prescott, 1988,

1990). The study’s design permits analysis of both

direct and indirect effects of NPD project planning

activities on innovation performance.

The different management variables that are ex-

plored may be characterized by relating them to the

so-called fuzzy front end of NPD (Khurana and

Rosenthal, 1997; Smith and Reinertsen, 1991). De-

spite the widespread use of this term, there seems to be

no universally agreed-on definition of the activities

and phases that the fuzzy front end actually entails.

Reid and de Brentani (2004), on the one hand, use the

term to denote the earliest phase of the NPD process,

that is, roughly equated to all the time and activity

spent on an idea prior to the first official group meet-

ing for the particular NPD project. Khurana and

Rosenthal (1998), on the other hand, state that the

front end entails all activities prior to the time that a

business unit commits to the funding and launch of a

NPD project or decides not to do so (i.e., go/no-go

decision). Khurana and Rosenthal assert that this go/

no-go funding decision is typically made after the

business case has been evaluated to assess the project’s

likely financial returns and after some degree of pro-

ject and risk planning has been carried out.

To capture the actual activities of product innova-

tion as specifically as possible, it is necessary to dis-

tinguish between two types of planning activities: (1)

predecision business planning; and (2) postdecision

project planning. At the beginning of NPD projects,

information is gathered with the aim of evaluating the

innovative idea and developing an initial understand-

ing of the business case. Typical involved in this

early-stage planning are a number of scanning and

analyzing activities that can be subsumed under the

term business planning (Zahay, Griffin, and Frede-

ricks, 2003). Following Mintzberg (1981, 1994), this

type of planning may also be characterized as prede-

cision planning because it is usually undertaken well

before it has been decided whether or not to launch

the actual product development process.

Although business planning is a typical element of

the front end of a NPD project, this article argues that

a second set of planning activities usually comes into

focus only after a decision has been made to com-

mence the actual product development process. Cen-

tral to this type of postdecision planning are detailed

project scheduling and task-oriented resource allo-

cation activities, hereafter summarized as project

planning. In addition, the specific uncertainties of

innovation projects must be addressed. Product inno-

vations are typically targeted toward unknown mar-

kets or employ new technologies with which the

organization has only limited experience. Venturing

into these uncertainties may expose innovating

organizations to increased risks. Consequently, a sec-

ond area of postdecision NPD planning activities is

NPD PLANNING ACTIVITIES AND INNOVATION PERFORMANCE J PROD INNOV MANAG2007;24:285–302

287

concerned with risk or contingency planning. Detailed

project planning and risk planning are viable only

after the development idea has been evaluated and

approval has been granted to initiate development.

Hence, project and risk planning should not be con-

sidered as elements of the fuzzy front end of NPD but

rather as an integral part of the subsequent imple-

mentation phase (i.e., back end).

This article addresses the interrelationship of differ-

ent NPD planning activities by a first set of hypothe-

sized relationships, H1 and H2, which suggest that

predecision business planning develops the basis for

the dimensions of operational postdecision planning, in

that proficiency of project and risk planning will in-

crease with a more thorough business plan. The second

set of hypotheses—H3, H4, H9, and H10—concerns

the direct performance effect that back-end variables

(i.e., postdecision planning and process management)

have on NPD performance. Process management in-

cludes, on the one hand, aspects of process formality

such as employing means to structure the development

process and using clearly defined decision rules. On the

other hand, process management focuses on the

amount of change regarding quality and time goals

and resource commitments. In addition to the direct

effects of planning on performance, relationships be-

tween project planning and process management are

suggested. Hence, H5, H6, H7, and H8 are concerned

with a mediated performance effect of project planning

through process management. The path model with the

relationships among NPD planning, process manage-

ment, and NPD performance is shown in Figure 1.

This study’s conceptual framework is based on or-

ganizational information processing theory. Accord-

ing to Souder and Moenaert (1992), innovation

processes can be defined as processes for reducing un-

certainty or, alternatively, as processes for collecting

and processing information. Viewing NPD projects

as information processing systems automatically

requires a contingency approach, because the infor-

mation requirements of a project are contingent upon

its task uncertainties. The more uncertain the task, the

greater the quantity and quality of information pro-

cessing required to generate the knowledge necessary

to execute the project successfully. Following the

definition of Galbraith (1973, 1977), uncertainty is

the difference between the amount of information

required to perform particular tasks and the amount

of information already possessed by the organiza-

tion. Hence, the degree of innovativeness can be

understood as a measure of task uncertainty, as it de-

scribes the difference between a status quo ante and

the actual innovation outcome on several dimension

of the new product.

As an additional premise of the present study,

therefore, it is hypothesized that the extent to which

project planning and process management can con-

tribute to project-level success is strongly dependent

on product innovativeness. For an NPD project to

perform well, the information processing capabilities

of the planning and management system must satisfy

the information processing requirements of the spe-

cific product innovation. Accordingly, a fourth set of

hypotheses, H11 and H12, speculates that the strength

Project planning

Business planning

Riskplanning

Goal stability

Innovation success

Degree of innovativeness(hypothesized to moderate paths)

H11 H12

Process formality

H1

H2

H3

H4

H10

H9

H7

H6

H5

H8

Figure 1.



of all performance relationships is moderated by the

degree of product innovativeness.

Business Planning as an Antecedent of ProjectPlanning

Early in the NPD process, the organization strives to

develop a concept of the future product and a rough

understanding of the business case for it (Clark and

Fujimoto, 1991; Zahay, Griffin, and Fredericks,

2003). Brown and Eisenhardt (1995) note that partic-

ularly important early-stage details include a prelim-

inary assessment of markets and technologies, a clear

product concept statement, and a well-defined target

segment. To build a sound business case, planning

must identify the main potential drivers of NPD

success (Browning et al., 2002). In addition, planning

must include an initial test to determine if the intend-

ed innovation exhibits a good fit with the firm’s strat-

egies and competencies; these analyses are crucial

prerequisites in determining whether or not the firm

should invest resources to further develop the inno-

vation idea (Cooper, Edgett, and Kleinschmidt, 2001).

Methodological issues also determine the proficien-

cy of early-stage planning. Planning that systemati-

cally searches for alternatives, develops these

alternative scenarios, and applies a rational selection

procedure helps to ensure effective concept develop-

ment and to increase the potential for NPD success

(Bordley, 1998; Osawa, 2003; Osawa and Murakami,

2002). In addition to the benefits of detailed and me-

thodically sound business planning, the process of

business planning itself may also have a positive per-

formance effect. Plans that are made in a vacuum by

senior management and dictated to the new project

team are likely to be met with distrust (Thieme, Song,

and Shin, 2003). However, if team members are in-

volved in the planning process they are more likely to

take ownership of the plan and to strive for its fulfill-

ment (ibid.). In addition to these motivational effects,

a participative planning process may also secure ad-

equate informational input. As uncertainties in differ-

ent areas may be high, involvement of a diverse set of

actors increases the richness of information and helps

to secure early validation of concepts (Olson et al.,

2001; Salomo, Gemunden, and Billing, 2003).

In the event that the organization decides to pro-

ceed beyond the stage of concept development, the

actual development stage is entered. This stage in-

volves the translation of product concepts into a

concrete product. Here, postdecision planning or

programming (Mintzberg, 1981, 1994) provides the

information necessary to implement and control plan-

ning decisions. It represents the multitude of functions

performed by planning to assist in the product devel-

opment process through information dissemination

and integration. Such postdecision project planning in

NPD is specifically concerned with the more opera-

tional planning activities targeted at analyzing and

planning for the actual development process. Project

planning will thus include, for example, a detailed

analysis of the work breakdown structure and the use

of milestone and resource plans (Meredith and Man-

tel, 1995; Rosenau and Moran, 1993). NPD projects

that are initially based on a sound and professional

business plan start with a more detailed understand-

ing of the business case and the intended product

(Bacon et al., 1994). Information that was generated

during the initial stage of the development process to

facilitate an informed decision whether or not to start

the NPD project also provides a sound basis for fur-

ther operational planning activities. Furthermore, it is

suggested that proficient business planning include a

diverse set of actors in the planning process itself,

helping to foster multifunctional information input

and enhanced team member commitment to taking

ownership of the planning process (Bacon et al., 1994;

Khurana and Rosenthal, 1997). Specifically, the effect

of committed team members as an outcome of the

business planning process will also help to promote

detailed project planning. Hence, because of more

proficient business planning, the proficiency of project

planning will increase.

H1: The proficiency of business planning is positively

related to proficient project planning.

As each NPD project is different and, by nature, in-

volves a degree of uncertainty that may lead to pos-

itive and negative impacts, risk planning is considered

to be another aspect of postdecision planning (Brown-

ing et al., 2002). The goal of project risk planning is to

forecast the various sources of risks, especially those

that are likely to have the most serious adverse

impacts on the NPD project, and to prepare for and

reduce their consequences (Jaafari, 2001; Wideman,

1998). Project risk planning can be divided into two

generic activities: (1) a risk analysis that focuses on the

identification and quantification of risk factors; and

(2) a risk- or contingency-planning activity that es-

tablishes a plan to monitor the actual progress of


289

project implementation constantly and to track

the effectiveness of risk response plans (Chapman,

2001).

Because both the procedural aspects and the con-

tent of business planning provide a sound basis for

postdecision risk planning (Chesbrough and Rosen-

bloom, 2001), this article suggests that more proficient

business planning improves the proficiency of project

risk planning.

H2: The proficiency of business planning is positively

related to proficient risk planning.

Direct Effects of Project Planning on InnovationSuccess

Project-planning and risk-planning activities are

concerned with project-level operations and help to

structure the NPD process and to provide develop-

ment teams with short- and longer-term goals. It

has been suggested that the more detailed the plans

regarding goals, timelines, hurdles, and responsibili-

ties, the greater the NPD performance (Dvir, Raz,

and Shenhar, 2003; Shenhar et al., 2002). Plans with-

out such details can be detrimental, as they may dis-

tract the NPD project team from performing the

appropriate activities and may create unnecessary

conflict between various individuals or parts of the

organization over these details (Thieme, Song, and

Shin, 2003). Hence, the following positive relationship

is proposed between project planning and NPD per-

formance:

H3: The proficiency of project planning is positively

related to project success.

Although not all projects face the same amount of risk

and because full-fledged risk management may be

necessary only for some high-risk projects, risk plan-

ning may still be necessary for all NPD projects (Raz,

Shenhar, and Dvir, 2002). Accordingly, such planning

activities facilitate evaluation of the actual risk situa-

tion and adjustment of risk management investments.

Hence, it is suggested here that projects that involve

detailed risk-planning activities should outperform

projects that proceed ignorant of potential risks.

H4: The proficiency of project risk planning is

positively related to project success.

Process Management as a Mediator betweenPlanning and Success

Process management is considered to include activi-

ties directed at managing the development process in

NPD projects. It has been widely studied to determine

the impact on NPD success of project structuring, as

evidenced by presence of milestone plans and Stage-

Gates processes (Cooper, 1990; Cooper and Klein-

schmidt, 1990). The formal structuring of NPD pro-

cesses along predefined decision gates with clearly

identified goals and decision rules is recognized as

an important element of process management (Rose-

nau and Moran, 1993; Wheelwright and Clark, 1992).

Consequently, process formality is one of the two

process management dimensions explored in the sug-

gested model. The second dimension captures the

degree of goal stability throughout the innovation

process (Hauschildt and Pulczynski, 1992; Lynn and

Akgun, 2001). Projects undergoing less frequent

changes of timing and resource commitments exhibit

process management activities that serve to prevent

such changes (Billing, 2003). This study hypothesizes

that process formality and goal stability affect NPD

success and, in turn, are influenced by the two dimen-

sions of postdecision planning. In particular, it is

suggested that process management mediates the re-

lationships between project and risk planning and

NPD success.

Project planning addresses issues concerned with

the actual management of the development process.

Planning resource commitments and work packages

results in a predefined structure for the overall devel-

opment process and allows project execution to pro-

ceed according to this structure. Hence, the tendency

to deviate from the initial plan to explore (e.g., side-

track opportunities along the way) will decline. Con-

sequently, goal changes due to such opportunistic and

random activity will become less frequent. As

project planning develops a plan for project execution,

process formality, as the actual outcome of this plan-

ning activity, should also be enhanced. Individual

qproject goals and necessary resources synthesized

through project planning provide the NPD project

team with detailed information to structure the devel-

opment activity adequately. The probability of NPD

teams actually relying on milestone plans and basing

their decisions on clearly defined criteria will increase

with more detailed and better specified project plans.

This article also considers risk planning—the sec-

ond dimension of operational NPD planning—to



have an effect on goal stability. For cases in which

intensive risk assessment and contingency planning

are performed, awareness of uncertainties and poten-

tial future impediments to reaching predefined project

goals may increase. Consequently, risk planning will

lead to a more realistic goal definition, thus reducing

the necessity of subsequent goal changes. In addition,

performing systematic risk analyses and developing

contingency plans will foster a structured process to

new NPD. More intensive risk management will

enable higher degrees of process formality.

Overall, goal stability throughout the development

process and process formality are indicators of pro-

cess management; in addition, they reflect the quality

of postdecision planning. Higher proficiency in both

planning dimensions (i.e., high-quality project and

risk planning) should result in less demand for alter-

ing project goals in the later project stages as well as in

potentially stronger process formality. Hence, the

following hypotheses are suggested.


related to goal stability.

H6: The proficiency of project risk planning is posi-

tively related to goal stability.


related to process formality.

H8: The proficiency of project risk planning is posi-

tively related to process formality.

This article proposes that goal stability, as an indica-

tor of process management and planning quality, has

a positive performance effect by itself. Strong changes

in project goals throughout the development process,

perhaps even resulting in a goal structure and content

completely different from what was initially intended

(Van de Ven, 1999), may have negative performance

effects. Any change in project goals regarding the

properties of the new product may make initial in-

vestments obsolete, and goal changes may result in

increased costs because of a need to adjust develop-

ment activities to accommodate the new goals (Ham-

el, 1974; Thomke and Fujimoto, 2000). As for indirect

negative effects, frequent goal changes may foster

frustration and disappointment among NPD team

members, adding to potential costs of this process

management dimension (Barczak and Wilemon, 2001;

Billing, 2003). Frequent goal changes may also be

interpreted as indicating that process management is

based on ad hoc decision making, thus allowing op-

portunistic pursuit of new options as they arise during

the development process. The limited ability to adhere

to previously set goals indicates problems with project

execution (Seibert, 1998). Consequently, development

time will increase and greater deviations from the ini-

tially approved business case will be allowed without

equally intensive up-front evaluation. Overall, there

would be an increase in the probability of ending up

with a solution that has fewer economic benefits than

otherwise would be the case if frequent goal changes

are allowed. On the other hand, no goal changes at all

may indicate strong rigidities in process management

(Thomke and Reinertsen, 1998; Verganti, 1999). Ab-

solute adherence to initially defined goals may signal

that the organization tends not to react adequately to

external and internal changes (Thomke and Reinert-

sen, 1998). If bounded rationality and uncertainties are

typical properties of innovation projects, a significant

reduction occurs in chances of achieving initial project

goals throughout the development process (Thomke,

1997). Hence, in the proposed positive relationship

between goal stability and NPD performance an al-

lowance must be made for a limited degree of change

in goals and, thus, a consideration must be made for

major goal fluctuations only. Recognizing this limita-

tion, the following hypothesis is proposed.

H9: Goal stability is positively related to project

success.

Formal control mechanisms for guiding and evaluat-

ing the project’s progress may be developed based on

the strategic business direction of the product inno-

vation and the project plan crafted in the early stages

of an NPD project. On the one hand, management

may establish specific goals for the project team to

attain on one or more outcome dimensions (i.e., out-

put control). On the other hand, management may

monitor the adherence to certain procedures and ac-

tivities specified in the project plan (i.e., process con-

trol) (Ouchi, 1979). The degree to which prespecified

rules and procedures govern product development

activities is typically referred to as process formality

(Tatikonda and Montoya-Weiss, 2001). Clear

evidence of process formality is typically signaled by

the use of a structured Stage-Gates system for man-

aging the development process (Cooper and Klein-

schmidt, 1990; Rosenthal, 1992). Installing such a

structured system offers a number of key advantages:

Schedule- and budget-based milestones tend to keep


291

teams aware of their scarce resources, and formal

reviews serve to guide decision making regarding

resource allocation (Wheelwright and Clark, 1992).

Process formality may aid development effectiveness

because a work process that incorporates controls and

reviews provides project personnel with a sense of

structure and sequence to the work, reducing ambi-

guity about what to work on and when (Rosenthal,

1992; Tatikonda and Montoya-Weiss, 2001). Thus,

H10: Process formality is positively related to project

success.

Degree of Innovativeness as Moderator

The results of empirical studies suggest that pro-

ject characteristics such as project uncertainty and

project complexity moderate project management–

performance relationships (Eisenhardt and Tabrizi,

1995; Lewis et al., 2002; Moorman and Miner, 1998;

Salomo, Steinhoff, and Trommsdorff, 2003; Shenhar

et al., 2002; Tatikonda and Montoya-Weiss, 2001).

Uncertainty and complexity of NPD is strongly relat-

ed to the degree of innovativeness. Although previous

research offers a wide range of different definitions of

innovativeness (Garcia and Calantone, 2002; Green,

Gavin, and Aiman-Smith, 1995), the degree of change

associated with the NPD project is generally a good

predictor of innovativeness. Such change is usually de-

fined separately on technology and market dimensions.

Moreover, recent research also suggests that innova-

tiveness is related to the degree of fit of internal and

external resources required to develop the new product

(Danneels and Kleinschmidt, 2001). With increasing

degrees of innovativeness come greater technological

discontinuities and greater market-related, organiza-

tional, and environmental changes. At its extreme, a

radical innovation will, for example, apply a totally new

technological principle, create a new market, reshape

the value chain, require totally new production methods

and facilities, and demand a new infrastructure for its

use (Salomo, Gemunden, and Billing, 2003).

Thus, greater degrees of innovativeness in a NPD

project brings with it stronger uncertainties. Project

planning serves to structure and coordinate work and

facilitates using a predefined, well-structured process

during development, a process that facilitates direct-

ing scarce development resources toward reducing

uncertainty in the most important areas. For exam-

ple, technology development or identification of mar-

ket needs receives sufficient attention as resources are

not consumed with organizing the process. Addition-

ally, well-defined processes ensure that regular tests of

essential requirements (e.g., business viability) are not

left to chance. As highly innovative NPD projects of-

ten venture into unexplored technological arenas, for

example, the probability of unexpected opportunities

occurring throughout development process increases,

making regular validity checks ever more necessary.

The increased importance of risk planning in cases of

high innovativeness is supported by arguments similar

to those used in discussing the importance of business

planning. Potential risks increase with higher innova-

tiveness, thus increasing the potential benefits of early

identification of uncertainties and timely implementa-

tion of contingency plans.

However, strong uncertainties are, by definition,

accompanied by limited or costly accessibility to

information. With a dearth of useful information

available at the beginning of a development project,

planning may become almost impossible or too costly.

Even if valid information can initially be generated

and plans crafted accordingly, highly innovative de-

velopment may evolve along an unexpected path, thus

requiring frequent or continuous information updat-

ing and generation of new information. In the most

extreme case, all resources will be diverted to planning

and replanning activities, prohibiting efficient and

effective product development. In fact, some results

from in-depth studies of the management of radical

innovations show that teams do not address all

uncertainties simultaneously but rather choose a se-

quential approach, thus reducing specific uncertain-

ties before moving to others (Leifer et al., 2000;

McDermott and O’Connor, 2002). Understandably,

teams working on radically innovative NPD projects

acknowledge their inability to cope with various

information demands simultaneously. Committing re-

sources to thorough planning in such a situation, con-

sequently, should not enhance project performance.

Overall, the net effect of planning activities on the

performance of highly innovative NPD projects re-

mains unclear. As this article argues for both positive

and negative effects of planning, the moderating effect

of innovativeness may be leveled out, leading to H11a

and 11b. However, whether or not these potential

positive and negative effects actually balance each

other remains a question for empirical analysis.

H11a: The positive relationship between project plan-

ning and project success is not moderated by the

degrees of innovativeness.



H11b: The positive relationship between risk planning

and project success is not moderated by the de-

grees of innovativeness.

This article suggests that the two dimensions of pro-

cess management affect NPD success positively. In

general this study assumes a positive effect of goal

stability on project success; however, complete stabil-

ity, as argued already, indicates rigidities in process

management. Organizations must maintain a certain

degree of flexibility to react appropriately to shifting

conditions. External changes (e.g., pioneering com-

petitors) or internal changes (e.g., technological

inventions based on serendipity) cannot be fully an-

ticipated through planning and must be accounted

for during project execution. Such unexpected

events are most likely to happen in projects involving

development of highly innovative products, thus pe-

nalizing NPD process managers for not allowing suf-

ficient goal flexibility. Because project goals for time,

budget, or intended quality are difficult to determine

in advance for highly innovative NPD projects, pro-

cess formality also becomes more difficult to achieve.

To a degree, process control may be detrimental if it

reduces a developer’s ability to cope with uncertain-

ties that arise in development projects—uncertainties

that arise as new market information becomes avail-

able, for example, or uncertainties resulting from

unanticipated technological problems (Eisenhardt

and Tabrizi, 1995).

H12a: The positive relationship between goal stability

and project success is stronger with low degrees

of innovativeness than with high degrees of

innovativeness.

H12b: The positive relationship between process for-

mality and project success is stronger with low

degrees of innovativeness than with high degrees

of innovativeness.

Research Methodology

Data Collection and Sample

The present study employs a cross-sectional survey

methodology to collected information from 132 NPD

projects. To build the sample, 144 companies were

contacted that had participated in an earlier study

investigating management activities in highly innova-

tive projects (Salomo, Steinhoff, and Trommsdorff,

2003). Of these 144 companies, 64 agreed to partici-

pate in the study. Additionally, companies that had

participated in an innovation competition organized

by German chambers of commerce were contacted by

phone and asked to participate in the survey, with the

focus on the innovation project they submitted for the

competition. Within each of the resulting 132 partic-

ipating companies, one NPD project was identified,

and the respective project manager was contacted by

phone to explain the intention of the study and to se-

cure a commitment. This phone contact was also used

to ensure that the project manager had been with the

project from the beginning or was very familiar with

the planning and control activities. These restrictions

assured that the respondent had a broad view of the

project and could provide the detailed technical

and management information required. Each project

manager was asked to complete a self-administered

questionnaire. Potential concerns about retrospective

bias and common methods variance were in part ame-

liorated via the instrument development process. This

process involved careful instrument design, with

particular attention paid to question wording and

sequence.

Measures

To test the hypotheses suggested by the conceptual

framework, measures of each construct were devel-

oped using multiple items and Likert-type scales

(15 strongly disagree to 75 strongly agree). An ex-

tensive literature review helped to identify relevant

concepts and previously operationalized scale items.

Although many items were derived from existing val-

idated scales, some items were developed specifically

for this study. All of the scales were refined or devel-

oped in collaboration with experienced project man-

agers, and the scales underwent two waves of formal

pretests to assure scale content validity and to obtain

preliminary data on the hypotheses. In the pretests,

all respondents completed a questionnaire, and five

respondents were involved in follow-up interviews.

Their comments and suggestions were used to revise

the questionnaire, such as to remove ambiguities and

other sources of confusion.

The resulting measurement scales were subjected to

a commonly used validation process to assess their

reliability, validity, and unidimensionality. Reliability

initially was evaluated using Cronbach’s alpha and

item-to-total correlations. Following the recommenda-

tion of Churchill (1979), items with low item-to-total


293

correlations were eliminated because they do not

share sufficiently in the construct’s common core.

Hereafter, all scales were subjected to a principal

components analysis with varimax rotation. Finally,

confirmatory factor analysis (CFA) was used to verify

the convergent and discriminant validity of the mea-

sures. In CFA, convergent validity is evaluated by the

significance of each standardized coefficient loading.

As a further check, the average variance extracted was

calculated for all constructs (Fornell and Larcker,

1981) and it was further used to assess discriminant

validity, demanding that it be greater than the

squared interscale correlations of the construct

(ibid.). As a second confirmation of discriminant va-

lidity, chi-square difference tests for all pairs of scales

were conducted, each time comparing a model in

which the correlation of the two constructs was

constrained to equal 1.0 with an unconstrained mod-

el. The individual scales, along with their items and

sources, are discussed following; statistical detail

for the scale validation is presented in the Results

section.

Proficiency of business planning was measured by

the scope or content of the initial planning activities

that are involved in establishing a business case and in

choosing the methodology used to derive such a plan.

The content of business planning is captured by three

items that measure the intensity of (1) identifying

main value drivers; (2) testing for fit with corporate

strategy; and (3) testing for fit with core competencies.

Methodological proficiency of business planning is

measured using six items covering the use of thorough

planning techniques and the tendency to take a par-

ticipatory planning approach. These items are based

on scales previously tested by Cooper and Kleinsch-

midt (1995) and Atuahene-Gima and Li (2004).

Proficiency of project planning is concerned with

planning the actual execution of development activi-

ties and focuses primarily on optimizing resource

allocation. Based on previously used measures

(e.g., Shenhar et al., 2002), project planning is cap-

tured by three items covering activities related to work

breakdown structures, milestone plans, and resource

plans.

Based on the risk-management scale employed by

Raz, Shenhar, and Dvir (2002), risk planning is cap-

tured through three items: (1) the extent to which risks

and their consequences are analyzed; (2) the compre-

hensiveness of plans to reduce uncertainty as the

major source of risks; and (3) the effort taken to

design detailed risk response plans.

Three items adapted from Covin and Slevin (1998)

and Lynn and Akgun (2001) were used to evaluate the

tendency of process managers to allow frequent goal

changes. The first two measures assess the amount of

change in project objectives, timetables, and resource

commitments. The third item measures the overall

deviation from initially planned goals.

The process formality scale is derived from mea-

sures previously tested by Bonner, Ruekert, and

Walker (2002), Lewis et al. (2002), and Tatikonda

and Montoya-Weiss (2001). Four items were used to

assess the degree to which product development was

managed as a formal top-down process. The first item

tested the extent to which the project team was as-

signed clear performance targets; two items asked

whether milestones were used to track the project me-

thodically and to take strategic decisions concerning

the project; and the last item assessed the existence

of clear, predefined criteria for strategic decisions

(e.g., continue or terminate the project, resource

allocation).

Although studies on project tasks and outcomes

often focus on project efficiency (e.g., Bonner, Rue-

kert, and Walker, 2002; Griffin, 1997), this research

took a broader approach and assessed project perfor-

mance along four dimensions, capturing product,

market, and financial success, as well as project effi-

ciency. The managers responsible for the project were

asked to evaluate project performance relative to the

original project goals using the success measures

previously employed by Griffin and Page (1993).

Although self-assessment measures may be prone

to bias, they are the most commonly used form of

performance assessment and have been shown to be

sufficiently reliable (Dawes, 1999; Dess and Robin-

son, 1984; Pearce, Robbins, and Robinson, 1987).

Furthermore, objective financial data were often not

available at the unit of analysis desired. Perceptual

measures also enabled performance to be assessed for

projects that had recently entered the market at the

time the survey was conducted.

Product innovativeness is the central moderating

variable in this research design. Following prior con-

ceptual and empirical research, a measure of innova-

tiveness was applied that covers aspects of product

and process technology, market characteristics, and fit

with internal and external resources. All items have

been used in previous research (Danneels and Klein-

schmidt, 2001; Gatignon et al., 2002; Green, Gavin,

and Aiman-Smith, 1995; Hauschildt and Schlaak,

2001), and the full scale was validated in an earlier



study (Salomo, 2003). First, by accounting for differ-

ent dimensions of innovativeness, and, second, by

including a macro perspective of innovativeness

through assessing specifically the fit with external

resources (Garcia and Calantone, 2002), it was possi-

ble to separate incremental from highly innovative

new products. The project manager was asked to as-

sess each aspect of product innovativeness as it was

experienced ex ante. To measure perceived newness

of, for example, product technology, respondents

were asked to evaluate separately, on a seven-point

Likert-type scale, the degree to which a new techno-

logical principle was applied, the extent to which tech-

nological performance was increased, and if the new

technology had superseded existing technologies.

Overall, 12 items are used to measure the four

dimensions of innovativeness.

Results

This study followed the recommendations of Anderson

and Gerbing (1988) and estimated a measurement mod-

el prior to testing the substantive hypotheses. Also, the

moderator hypotheses were tested only after the main

effects had been assessed. Hence, the empirical analysis

was done in the following three stages: a measurement

model, a path model containing the main effects, and a

model testing the moderator hypotheses.

Measurement Model

First, the reliability of the constructs was assessed by

calculating alpha coefficients (see the Appendix). They

range from .77 to .94, a range considered to be highly

satisfying given the fact that some of the constructs

comprise only three items (Hair et al., 1998). Thereaf-

ter, all scales were subjected to principal components

analyses. In each case only the first eigenvalue was

greater than one, providing support for the unidimen-

sionality of the constructs (Ahire and Devaraj, 2001).

Convergent and discriminant validity were demonstrat-

ed by a series of CFAs using LISREL. All standardized

factor loadings were significant, indicating convergent

validity. Discriminant validity was confirmed by the

fact that, for each pair of constructs, the average vari-

ance extracted was greater than the squared interscale

correlations, and a measurement model with uncon-

strained correlation between the scales led to a signif-

icantly better fit than for a model in which the

correlation was constrained to being equal to 1.0.

Main Effects Model

In stage two a full structural equation model using

LISREL was performed to assess the hypothesized

main effects among NPD project planning, process

management, and innovation success. Table 1 pre-

sents correlations between all constructs and includes

mean values, standard deviations, and Cronbach’s al-

phas for each scale. Table 2 reports the results from

the path model estimating the main effects of the in-

dependent variables on innovation success.

To evaluate the fit of the model, a two-index pre-

sentation strategy was followed reflecting recent re-

search by Hu and Bentler (1998, 1999). Both the

comparative fit index (CFI) and root mean square

residual (SRMR) values obtained are well within the

bounds recommended by Hu and Bentler’s simulation

studies, thus allowing interpretation of the results. H1

and H2 are supported by the data, suggesting a pos-

itive effect of proficient business planning on the two

postdecision planning activities, project planning, and

risk planning. Of the hypothesized four direct perfor-

mance effects from the two planning activities and the

two process management dimensions, only two main

Table 1. Sample Descriptive Statistics and Correlationsa

Variable Mean S.D. 1 2 3 4 5 6 7

1. Degree of Innovativeness 3.45 0.98 (.78)2. Project Success 5.06 0.96 � .09 (.80)3. Proficiency of Business Planning 4.70 1.16 � .02 .41�� (.84)4. Proficiency of Project Planning 5.20 1.47 � .16 .30�� .57�� (.87)5. Proficiency of Project Risk Planning 4.35 1.71 .11 .53�� .64�� .51�� (.94)6. Process Formality 5.20 1.33 .10 .37�� .58�� .72�� .58�� (.82)7. Goal Stability 4.63 1.33 � .19� .57�� .41�� .46�� .47�� .47�� (.77)

a Cronbach’s alpha reported along the diagonal.� po.05.�� po.01.�� po.001.


295

effects show significant and positive path coefficients.

The proficiency of project risk management (.35) and

goal stability (.43) exhibit a positive and significant

relationship with innovation success, thus supporting

H4 and H10. Neither the proficiency of project plan-

ning nor process formality has a significant direct

effect on NPD performance. H5–H8 suggest that

process management activities mediate the planning–

performance relationship. The data support these

hypotheses as proficiency of project planning and

risk planning prove to be positively related to goal

stability and process formality.

Moderating Effect of Product Innovativeness

To assess the moderating effect of degree of in-

novativeness on the proposed main relationships of

planning and process management with innovation

success, a moderated multiple regression analysis was

performed (Aiken and West, 1991). Due to restric-

tions based on otherwise inadequate sample-to-

variable ratios (Hair et al., 1998), the decision was

made to regress the planning and process manage-

ment constructs separately on innovation success.

Results of the moderating effect of innovativeness

on the planning–performance relationship are pre-

sented in Table 3, and findings for the process man-

agement activities are presented in Table 4.

Consistent with the results from the path model, all

main effects regressions show significant F-values

and, consequently, allow interpretation. Overall, the

two different postdecision planning activities explain

27 percent of the performance variance. However,

only the proficiency of project risk planning shows a

significant and positive beta. Adding the interaction

Table 2. Standardized Path Coefficients and Fit Statistics—LISREL Analysisa

Dependent Variable Predictor H Coefficient Conclusion

Proficiency of Project Planning Proficiency of Business Planning H1 0.57 H1 confirmedProficiency of Project Risk Planning Proficiency of Business Planning H2 0.65 H2 confirmedInnovation Success Proficiency of Project Planning H3 –0.11 (n.s.)

Proficiency of Project Risk Planning H4 0.35 H4 confirmedProcess Formality H9 0.05 (n.s.)Goal Stability H10 0.43 H10 confirmed

Process Formality Proficiency of Project Planning H7 0.58 H7 confirmedProficiency of Project Risk Planning H8 0.29 H8 confirmed

Goal Stability Proficiency of Project Planning H5 0.30 H5 confirmedProficiency of Project Risk Planning H6 0.32 H6 confirmed

aCFI5 0.99; SRMR5 0.053.

Table 3. Results of Hierarchical Moderated Regression—Innovation Success

a

Innovation Success

Model 1a Model 1b Model 1c

Main EffectsProject Planning .04 .00 .00Project Risk Planning .49�� .52�� .52��

ModeratorDegree of Innovativeness � .14� � .14�

Interaction TermsINNOV � Project Planning � .12INNOV � Project RiskPlanning

.02

R2 .28 .30 .31Adjusted R2 .27 .28 .28DR2 .28 .02 .01F 23.1�� 16.8�� 10.4��

a Standardized beta values are reported.� po.10.�� po.001.

Table 4. Results of Hierarchical Moderated Regression—Innovation Successa

Innovation Success

Model 2a Model 2b Model 2c

Main EffectsProcess Formality .14�� .14�� .16��

Goal Clarity .48�� .49�� .45��

ModeratorDegree of Innovativeness(INNOV)

.02 .03

Interaction TermsINNOV � Process Formality � .19�

INNOV � Goal Clarity .04

R2 .34 .34 .37Adjusted R2 .33 .32 .34DR2 .34 .00 .03F 30.0�� 19.9�� 13.2��

a Standardized beta values are reported� po.10.�� po.05.�� po.001.



terms of innovativeness and planning to the regression

does not increase explained variance significantly,

thus supporting H11a and H11b.

Regressing the two process management activities

on innovation success explains 33 percent of the per-

formance variance. Contrary to the study’s path mod-

el, process formality also has a positive but weakly

significant effect on innovation success. Again, adding

the interaction terms to test H12a and H12b does not

increase R2 significantly. However, the interaction of

process formality and innovativeness shows a nega-

tive and significant beta value. H12a is consequently

not supported by the data. H12b suggests a suppress-

ing effect of innovativeness on the process formality

performance relationship, and this effect is partially

supported.

Discussion

The primary aim of this study is to investigate the ef-

fects of planning and control on performance of NPD

projects. It was hypothesized that (1) thorough busi-

ness planning (i.e., predecision planning) creates a ba-

sis for proficient project planning and risk planning;

(2) the proficiency of project and risk planning as well

as process management activities each improves in-

novation performance directly; (3) the relationship of

planning and success is mediated by process manage-

ment; and (4) the strength of these relationships is

moderated by uncertainty as determined by the degree

of innovativeness. To test the hypotheses, data from

132 NPD projects were collected and analyzed. A

measurement model was used to establish valid and

reliable constructs, a path model to test the main ef-

fects, and a multiple-moderated regression analysis

for the moderator hypotheses.

The results concerning the effects of business plan-

ning on postdecision planning activities support H1

and H2. Thorough business planning has a positive

impact on the proficiency of project and risk planning.

NPD projects that initially identify the main value

drivers based on methodological analysis, that sys-

tematically develop alternative new product concepts,

and that select the most adequate alternative based on

strategy and competencies fit create sound bases for

more operational planning activities (Song and Mon-

toya-Weiss, 1998). Hence, proficiency of business

planning helps to improve both the content and the

process of subsequent planning activity. As both

project and risk planning show direct and indirect

positive performance effects, business planning as an

antecedent of more development-related planning is a

relevant activity for NPD.

Regarding the potentially alternative mediated per-

formance effects of business planning, this study’s

model is somewhat limited. Because business planning

is measured as the proficiency for initially detecting

main value drivers to establish an early and sound

understanding of the business case, it may also affect

performance through mediators other than those as-

sessed in this model. Business planning typically fo-

cuses on specific market advantages and technological

features unique to the innovation. Hence, it may, for

example, facilitate a better understanding of the need

to generate focused market information or to develop

technologies in cooperation with third parties. As a

consequence, one might expect business planning to

foster stronger market orientation and specific tech-

nology development activities, factors that have been

shown to improve NPD performance (Atuahene-

Gima, 1995; Gemunden, Heydebreck, and Herden,

1994; Narver and Slater, 1990). Thus, to detect addi-

tional indirect performance effects of business plan-

ning, these NPDmanagement activities would need to

be assessed as mediators. However, such analyses are

beyond the scope of this article.

This study’s hypotheses suggesting direct relation-

ships of planning activities and NPD success are sup-

ported only for cases in which project risk planning

exhibits a positive performance effect. Risk planning

obviously helps to minimize the detrimental effects of

uncertainties about negative impacts through initial

risk analysis and adequately directed contingency

planning. Although not all projects may be challenged

by adverse risks, such planning activity may help to

gain a better understanding of critical development

parameters. Managers of projects that have mecha-

nisms for creating awareness for potential risks are

better equipped to avoid potentially dangerous situa-

tions or are able to react more quickly through pre-

defined contingency plans. Hence, risk planning as

an essential part of postdecision planning in NPD

improves performance in general.

Contrary to risk planning, proficiency of project

planning has no significant direct impact on innova-

tion success. This lack of relationship may be caused

by the general problem of planning development ac-

tivities in innovative situations (Song and Montoya-

Weiss, 1998). As innovation, by its nature, exposes

organizations to uncertainty, it may be difficult

and costly to obtain the information required for


297

proficient project planning. Hence, more resources

need to be allocated for information generation and

processing to achieve viable NPD plans. The lack of a

performance effect may thus be caused by a percep-

tion that the costs of planning neutralize its benefits.

However, such detrimental effects of innovativeness

on the project–planning performance relationship

should increase with greater degrees of innovative-

ness. But this outcome is not supported by this study’s

results, which show a nonsignificant moderation ef-

fect of degree of innovativeness.

On the other hand, the failure to discover a direct

performance effect of project planning may occur

because project planning and performance are

disconnected through time and because numerous

intervening management activities are implemented

throughout the development process. Consequently,

the performance effects of planning proficiency need

to be assessed by accounting for potential mediators.

These results suggest that process management is a

mediator. Proficiency of project and risk planning

positively affect goal stability and process formality,

factors that are positively related to NPD perfor-

mance. NPD projects that rely on proficient project

plans and risk plans and, thus, have allocated to them

sufficient planning resources have better managed

subsequent development processes and result in im-

proved performance. Hence, these planning activities

improve NPD performance indirectly through facili-

tating better process management.

This study’s results provide some support for the

hypothesis suggesting a positive performance effect

for process management. However, process formality

shows a significant impact on innovation success only

in the regression analysis. As the significant and neg-

ative interaction term of process formality and inno-

vativeness suggests, this limited impact may be due to

a moderation effect. In cases involving highly inno-

vative NPD projects, activities like prestructuring of

processes and controlling of development activities

along predefined milestones may not be possible. Such

process management activities may even impose ri-

gidities that hinder project managers from reacting

opportunistically on detection of unexpected external

or internal developments.

Goal stability, on the contrary, proves to enhance

NPD performance strongly. As the measure of goal

stability allows limited flexibility, these results suggest

that NPD projects with strong fluctuations in their

project goals throughout the development process

prove to be less successful. This positive effect of

goal stability holds true for both incremental and

highly innovative projects. The moderator hypothesis,

suggesting that with increased degrees of innovative-

ness more goal flexibility will be needed, is not sup-

ported by the results. Overall, it was possible only

to a limited extent to detect hypothesized moderator

effects. However, these results should be interpreted

with caution. In the case of planning and goal stabil-

ity, the nonsignificant moderator effects may be the

result of positive and negative effects of these activ-

ities in highly innovative situations which add up

to a zero net effect. On the other hand, research has

shown that multiple moderating regression analysis—

analytically the most adequate tool (Aguinis, 1995)—

to be highly prone to Type II error, that is, to rejecting

a moderator hypothesis even though in reality

moderating effects are at work (McClelland and

Judd, 1993). Range restriction on the innovativeness

measure may be a potential artifact that influences the

power of the multiple moderated regression analysis

performed in this study (Aguinis, 1995; McClelland

and Judd, 1993). Although care was taken in the pres-

ent study to include some highly innovative projects

in the sample, the relatively low mean value of this

variable and its limited variance suggest that if a

greater number of highly radical innovations were

included, moderating effects of innovativeness may

be detected.

Limitations

In addition to the aforementioned issues concerning

model structure and potential range restrictions for

the innovativeness measure, this study has other

limitations. The measures of the different aspects of

planning, process management, and innovation

performance are perceptual, based on key informants.

The study relied on perceptual measures, as it is dif-

ficult to obtain objective and comparable measures

for the innovation process-related constructs of the

study across multiple firms and industries. Further-

more, perceptual performance measures, at least

on the firm level, seem to be highly correlated with

objective measures. In their seminal article, Dess and

Robinson (1984) report correlations in the range of

.48 to .69. Nevertheless, even these correlation results

indicate that perceptual measures are merely a partial

representation of objective performance measures.

Moreover, the data are gathered from the vantage

point of key informants. Although project managers



can be considered to be well-informed respondents

with respect to planning, process, and performance

issues, the study cannot control for the problem of

common method variance. Future research may fruit-

fully explore this issue in more detail and use multiple

respondents for each of the constructs. Another lim-

itation concerns the use of retrospective data. Bias

from this source was minimized by surveying manag-

ers who were responsible for the particular innovation

projects. To limit the recall time frame, projects were

allowed to enter the sample only after a market launch

of the new product had occurred during the previous

year. Still, it may be a valuable approach for future

research to employ a longitudinal research design to

assess planning and project management activities

during the process and subsequently to relate them

to the final innovation outcome using this study’s

proposed mediated model structure.

Conclusions

In sum, the results suggest that both proficiency of

development-related planning measures and process-

management measures are important predictors

of NPD performance. Specifically, goal stability

throughout the development process and proficiency

of project risk planning prove to enhance perfor-

mance significantly. The proficiency of development

related planning activities, like project planning and

risk planning, is positively related to business plan-

ning. Predecision business planning obviously is an

important antecedent of project and risk planning,

thus showing positive but indirect NPD performance

effects.

In addition, the results lend support to the hypo-

theses of a mediating role for process manage-

ment in the planning–performance relationship.

Project planning and risk planning support the qual-

ity of process management and, thus, impact NPD

performance indirectly.

Whether or not all results hold true for the highly

innovative situation is not at all clear. Planning seems

to be relevant also during development of highly in-

novative products. But the establishment of relatively

static process structures and adherence to predefined

development routines seem to be less adequate in

a situation of highly innovative NPD. However,

relatively stable project goals and planning activities

specifically concerned with identifying potential risks

and defining suitable contingency plans seem to be

relevant, independent of the degree of innovativeness.

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Appendix. Measurement Items and Construct Characteristics

Constructs and Items Lambda-X Standardized Loadings t-Values

Predecision Planning: Proficiency of Business Planning (CFI5 0.97, SRMR5 0.046)Overall, the analysis was thorough and methodical. .83 9.91We identified the main value drivers. .65 7.40Alternative market scenarios were considered. .74 8.63Systematic identification of alternative product concepts .85 10.11Systematic selection of preferred product concept .96 11.68Fit with corporate strategy evaluated .83 11.45Fit with core competencies evaluated .97 15.14Participation of relevant departments in planning process .68 6.39Team committed to project goals .90 7.67

Postdecision Planning (CFI5 0.99, SRMR5 0.047)Proficiency of Project Planning

We designed and used a work breakdown structure. .81 10.52We designed and used a milestone plan. .98 13.61We designed and used a resource plan. .71 8.91

Proficiency of Project Risk PlanningAnalysis of risks and their consequences .89 12.71Detailed plans for uncertainty reduction .95 14.04Detailed risk response plans .88 12.50

Process Management (CFI5 0.99, SRMR5 0.042)Process Formality

Process managed according to milestone plan .91 12.28Strategic decisions were taken at milestones. .69 8.41Project team was assigned clear performance targets. .82 10.61Clear, predefined criteria existed for strategic decisions. .64 7.62

Goal StabilityCore objectives and timetable only infrequently altered .83 8.93Resource commitments only infrequently adjusted .74 8.08Current project goals still correspond to original ones. .60 6.60

Innovation Success (GFI5 0.93, SRMR5 0.063)Product Dimension

Technical performance attained relative to objectives .57 6.16Product quality attained relative to objectives .91 9.57Manufacturability attained relative to objectives .57 6.16

Market DimensionSales attained relative to objectives .87 11.13Market share attained relative to objectives .80 9.98Competitive advantage attained relative to objectives .78 8.95

Project EfficiencyMet planned budget .56 6.22Met timetable .85 9.72Met time to market .71 8.58

Degree of Innovativeness (GFI5 0.98, SRMR5 0.060)Internal Resource—Fit

Redirection of corporate strategy .72 8.76Change in organizational structure .78 9.90Change in corporate processes .82 10.52Change in organizational cultural .76 9.51

External Resource—FitNew infrastructure .72 8.24Alterations in regulation .91 10.62Critical debate in society .61 6.98

Technology DimensionNew technological principle .57 4.97Increase in technological performance .72 5.70Unique competitive advantages .35 3.20

Market DimensionChange required in customer behavior .97 15.14Learning effort required from customer .63 7.76



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