Document [original]

J Prod Innov Manag. 2021;38:447–472.

447

wileyonlinelibrary.com/journal/jpim

Received: 14 May 2020

Accepted: 21 April 2021

DOI: 10.1111/jpim.12585

ORIGINAL ARTICLE

Rapid validity testing at the front end of innovation

BirgitPeña Häufler1

DietfriedGlobocnik2

PaolaLandaeta Saldías1

SørenSalomo1,3

This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original

work is properly cited.

1Chair of Technology and Innovation

Management, Technische Universität

Berlin, Berlin, Germany

2Department of Innovation Management

and Entrepreneurship, Alpen- Adria

Universität, Klagenfurt, Austria

3Center for Entrepreneurship, Danish

Technical University, Copenhagen,

Denmark

Correspondence

Birgit Peña Häufler, Chair of Technology

and Innovation Management, Technische

Universität Berlin, Straße des 17. Juni

135, 10623 Berlin, Germany.

Email: birgit.penahaeuf[email protected]

Associate Editor: Anna Cui

Abstract

To efficiently and effectively reduce the uncertainty inherent in the front- end of in-

novation processes, recent literature emphasizes new approaches that facilitate rapid

knowledge generation and learning such as design thinking, lean innovation, and pre-

totyping. However, these approaches differ in their conceptualizations and, despite

their popularity, the empirical evidence on the performance relevance of such ap-

proaches for established organizations is limited. In this research, we propose rapid

validity testing (RVT), in which we conceptualize and harmonize existing approaches

toward a unique and comprehensive set of front- end activities necessary to reduce

uncertainty and equivocality inherent to this phase and enable planned flexibility.

Drawing on information processing theory, we argue that organizations implement-

ing RVT also increase the probability of achieving innovation outcomes of superior

quality on time and within budget. We further argue that the effectiveness of RVT

depends upon internal and external environmental factors. Drawing on multirespond-

ent data collected from 1022 informants in 129 firms, we find empirical evidence that

organizations implementing the RVT approach in their innovation activities achieve

higher performance of their innovation programs, and that the performance relevance

of RVT depends upon technological turbulence and the organization's long- term ori-

entation and risk propensity. We contribute to the literature by conceptualizing RVT

as a set of activities that enable planned flexibility. Furthermore, we overcome empir-

ical shortcomings of studies on popular approaches that relied primarily on anecdotal

or case study evidence and imply the generalizability of their effectiveness. Our find-

ings highlight that organizations indeed not only benefit from RVT but also challenge

the notion of a one- size- fits- all approach to the front end of innovation.

KEYWORDS

environmental turbulences, experimentation, formalization, front end, innovation process,

organizational culture, planned flexibility, prototyping, rapid validity testing

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RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

INTRODUCTION

The main body of literature on the front end of innovation

(FEI) agrees on the relevance of this early phase for innova-

tion success and fuzziness as its main defining characteristic

(Eling & Herstatt, 2017; Kim & Wilemon, 2002a, 2002b;

Reid & de Brentani, 2004). The main causes of this fuzziness

are traced back to uncertainties about how an idea for a new

product, process, or service will be received by its intended

users once it is implemented (Schweitzer et al., 2018), the ac-

tivities that will lead to the implementation of the idea (Eling

& Herstatt, 2017), and the exogenous and endogenous ele-

ments (resources, contingencies, etc.) that will influence this

phase (Zhang et al., 2019). This fuzziness is aggravated by the

nonlinearity of the processes required to reduce uncertainty

at the FEI, which is characterized more often by iterative and

simultaneous learning processes (Chappin et al., 2019) rather

than a stepwise approach toward the final configuration of

the concept to implement (O'Connor & DeMartino, 2006).

The early validation of ideas as to their feasibility and poten-

tial has been identified as a key determinant of the success

or failure of innovation processes (Schweitzer et al., 2018;

Williams et al., 2019).

Frameworks like agile project management (Highsmith,

2009) and agile- stage- gate processes (Cooper & Sommer,

2016), embedded in innovation management literature, offer

general principles on how to enable iterative learning and

development in the entire innovation process to guide the

refinement of ideas (Brock et al., 2020). Previous research

on the particular FEI process, which is the focus of this

study, has shown evidence on the feasibility of addressing

this phase as “the resolution of a series of problem- solving

cycles” (Buganza et al., 2009, p. 310) in an efficient way

(Cooper, 1990) while allowing for the flexibility needed to

operate under dynamic environments (Buganza et al., 2009).

Consequently, particular approaches have emerged, among

which figure pretotyping (Savoia, 2019), prototyping (Bogers

& Horst, 2014; Mascitelli, 2000), lean innovation (Blank,

2013; Ries, 2011), and design thinking (Brown, 2008), which

also enjoy wide popularity in practice.

These practices have mostly been developed and studied

in isolation and, when looking at their application, are char-

acterized by their lack of concreteness: They materialize, as

“bundle(s) of attitudes, tools, and approaches” (Brock et al.,

2020; Liedtka, 2015, p. 929; Ries, 2011; Solaimani et al.,

2019). Commonalities in their defining elements can be ob-

served, as in the case of the application of prototyping, but

no consistent set of elements underlying these approaches

have been conceptualized and assessed with respect to their

innovation performance effect. This lack of a comprehensive

conceptualization limits our understanding of the defining el-

ements that enable an iterative learning and development pro-

cess at the FEI. Thus, it is currently difficult to propose a set

of particular actions necessary to implement rapid learning

and development in the FEI at the organizational level as well

as to investigate the effectiveness of such an implementation.

Linked to the latter, a second shortcoming of this body

of research is that despite the popularity of approaches such

as design thinking and lean innovation among scholars and

practitioners, empirical evidence of their effectiveness in fa-

cilitating the performance of the FEI remains limited. With

few exceptions (e.g., Cui & Wu, 2017; Roth et al., 2020), the

majority of the empirical validation of these approaches relies

on anecdotal evidence and qualitative case study designs, giv-

ing rise to calls for quantitative evidence by scholars (Elsbach

& Stigliani, 2018; Nakata & Hwang, 2020; Solaimani et al.,

2019). Furthermore, prior studies have mainly investigated

these approaches in the context of single innovation initia-

tives of start- ups and small businesses (Blank, 2013; Nakata

& Hwang, 2020), equally contributing to the limited basis

for generalization of their effectiveness (Elsbach & Stgliani,

2018; Liedtka, 2015; Razzouk & Shute, 2012). Although

proponents of these approaches frame them as ultimate silver

bullets to overcome the challenges of the FEI, others see them

just as another management fad (e.g., Johansson- Sköldberg

& Woodilla, 2009). Whether established organizations in-

vesting in the broad implementation of such approaches will

also benefit by increasing overall innovation performance

Practitioner Points

• The rapid validity testing (RVT) concept proposes

an approach to the front end of innovation based

on the premise of planned flexibility, or the bal-

ance of anticipation and reaction capabilities, to

address the fuzziness inherent to this phase of in-

novation processes.

• We provide a set of activities that go beyond what

is proposed by popular approaches, such as de-

sign thinking or lean innovation, and empirical

evidence on their effectiveness to facilitate inno-

vation projects to meet goals on time and within

budget.

• To achieve superior outcomes, the RVT approach

emphasizes the relevance of problem framing,

prototyping for testing and communication, user

integration, product, and business model itera-

tions; in addition, it stresses the relevance to in-

tegrate commercial learning, that is, feasibility

and economic considerations, in this early stage,

which is not an integral part of prior approaches

and prevents overstressing customer needs solu-

tion fit at the cost of technical, economic, and

commercial aspects.

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PEÑA HÄUFLER Et AL.

remains unclear. Generalization also requires taking contin-

gencies into account, which past research has yet failed to

provide (Nakata & Hwang, 2020). Our knowledge on which

factors of the internal and external environment of the orga-

nization influences reaping benefits from implementing such

approaches, is equally, at best, limited.

These gaps give rise to the following two research ques-

tions of this study: How can we conceptualize a comprehen-

sive set of activities, going beyond individual practices that

enable iterative learning and development in the FEI? What

is the performance relevance of this concept for established

organizations and does this depend upon their internal and

external environment?

To address the first question, we build on Verganti’s (1999)

planned flexibility framework to extract and organize defin-

ing elements and to develop rapid validity testing (RVT) as a

theoretically grounded concept. In order to answer the second

research question, we apply organizational information pro-

cessing theory (Daft & Lengel, 1986; Mackenzie, 1984) to

hypothesize how RVT is related to innovation performance.

In particular, we argue how the elements of RVT facilitate

outcomes of the innovation project portfolio in terms of meet-

ing objectives on time and within budget. Next, we argue on

the generalizability of the proposed RVT– performance rela-

tionship. On the one hand, we take industry differences into

consideration with respect to the market and technological

environment that might impact the effectiveness of RVT.

On the other hand, we consider the long- term orientation

and risk propensity of the organization. As previously noted,

scholars emphasize the universal application of practices

such as lean innovation and design thinking but have devel-

oped and studied those mainly in the context of start- ups and

small businesses. We recognize that small, entrepreneurial,

and established organizations face different internal contexts

(Ganco & Agarwal, 2009) and therefore consider these in-

ternal contingency factors that take differences in time hori-

zons and risk attitudes into account. These contingencies are

presumed to vary more between established organizations as

opposed to firms in the founding or entrepreneurial stage.

Finally, we empirically test our hypotheses with multirespon-

dent data collected from 1022 informants from 129 firms.

Our contribution to the literature is twofold: First, we

join the conversation on how to enable the organization to

effectively master the challenges associated with the FEI and

develop the concept of RVT. With its seven core, activity-

based elements that contribute to an optimal balance of antic-

ipation and reaction capabilities to enable planned flexibility

in the FEI, RVT goes beyond what has been proposed by

prior individual practices such as lean innovation, prototyp-

ing, design thinking, and pretotyping. RVT aggregates prior

approaches, closes gaps in their defining elements, and pro-

vides a comprehensive bundle of activities that can function

as a blueprint to study the strength and weaknesses of prior

approaches. Second, we provide empirical evidence on the

positive relationship between RVT and FEI performance

and its contingency upon factors of the internal and external

environment of the organization. Thereby we contribute to

the ongoing discussion of whether organizations that apply

approaches facilitating iterative learning and development

in the FEI actually benefit from such measures at the inno-

vation program level, drawing on more than just anecdotal

and case study- based evidence. The identified contingencies

also contribute to a clearer understanding of which organi-

zations may benefit more than others from implementing

RVT. Consequently, we highlight the need for future studies

to consider factors of the internal and external environment

to obtain a fine- grained picture on the effectiveness of RVT

and related concepts.

THEORETICAL FOUNDATION

2.1

Rapid validity testing: A conceptual

outline

Planned flexibility, as conceptualized by Verganti (1999),

denotes the organizational capability of combining and bal-

ancing anticipation and reaction capabilities in order to iden-

tify sensitive issues in a project and deliberately anticipate

and prompt actions to address these issues. This concept of-

fers an approach to address the information processing needs

of the front end of innovation as highly uncertain, highly

equivocal processes. Anticipation capabilities refer to the use

of approaches that engage users in cycles of trial- and- error

learning (von Hippel & Katz, 2002), the early inclusion of

relevant stakeholders (Bogers & Horst, 2014; Buchenau &

Suri, 2000; Klemmer et al., 2006), and the use of management

tools like target life cycle and target costing (Verganti, 1997,

1999). Reactive capabilities are conceptualized by Verganti

as resource flexibility, overlapped development activities,

and resource slack (Verganti, 1997, 1999). Possessing and

deploying anticipation capabilities will contribute to address

uncertainty by identifying, gathering, and analyzing relevant

information as early as possible in the process. The capabil-

ity to rapidly pivot and introduce changes once the process

underway supports the organization in counteracting equivo-

cality (Verganti, 1999).

A close examination of the particular FEI practices en-

abling planned flexibility, that is, pretotyping (Savoia, 2019),

prototyping (Bogers & Horst, 2014), lean innovation (Ries,

2011), and design thinking (Brown, 2008; Carlgren et al.,

2016; Hassi & Laakso, 2011), through the lens of Verganti's

conceptualization reveals that each approach provides par-

ticular activities for anticipation and reaction, which are

summarized in Table 1. No approach covers all aspects put

forward by the concept of planned flexibility, and they only

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show commonalities with respect to testing of assumptions

through continuous experimentation and prototyping and the

use of prototypes as an internal communication tool as well

as an instrument for user involvement (Bogers & Horst, 2014;

Carlgren et al., 2016; Savoia, 2019). As shown in Table 1,

our conceptualization systematizes approaches existing in

literature along with planned flexibility capabilities as iden-

tified by Verganti (1999) and, by including early evaluation

of market potential, pricing, and implementation costs as an

anticipation capability, goes beyond those proposed by the

popular approaches listed above. In light of the scattered re-

search landscape delineated in the previous sections, which

provides, at best, sets of normative statements with little em-

pirical validation, our proposed RVT concept offers, thus, a

comprehensive systematization of activities at the FEI that

goes beyond those proposed by the popular approaches listed

above.

Together, the activities determine the concept of RVT,

which represents a balance between anticipation and reaction

(Verganti, 1999). Such a balance epitomizes a planned ap-

proach to the activities at the FEI processes (Salomo et al.,

2007), while allowing for the flexibility necessary to accom-

modate the information that may emerge early on in the in-

novation process.

Verganti (1997, 1999), lists multiple mechanisms behind

anticipation and reactive capabilities. Mechanisms linked to

anticipation are the application of existing knowledge to the

early identification of critical areas of the product life cycle,

the early inclusion of relevant actors, and the encouragement

of proactive thinking through early prototyping and the ap-

plication of management tools to estimate future costs. RVT

elements corresponding to anticipation through the applica-

tion of existing knowledge are as follows: (i) The early es-

tablishment of central assumptions. This refers to developing

hypotheses on business and technical aspects of the idea an-

ticipated as crucial to the success of its realization and to be

validated over the course of FEI activities. At the FEI, the

knowledge available to generate assumptions typically builds

on experiences with past projects, and thus the ability to ac-

tivate and apply this knowledge to new projects at the FEI

becomes a crucial capability (Verganti, 1997). The second

and third elements of RVT are (ii) prototypes as an internal

communication tool to visualize, assess, and communicate

the concept with internal stakeholders, and (iii) user integra-

tion through prototype tests and other assessment techniques:

Prototypes increase the visibility of concepts, opening op-

portunities for the exchange of information with users (Cui

& Wu, 2017) and across functional departments (Bogers &

Horst, 2014) that may contribute to create clarity on inter-

nal and external potential barriers or opportunities (Bogers

& Horst, 2014; Verganti, 1997). As such, prototypes have a

dual purpose: on the one side, communicating, in a more tan-

gible way, the vision of the organization in a specific context

TABLE 1 Synoptic overview of approaches to planned flexibility and defining elements of RVT

Planned flexibility

capabilities (Verganti,

1999) RVT elements RVT labels

Pretotyping

(Savoia,

2019)

Prototyping (Bogers

& Horst, 2014)

Lean

innovation

(Ries, 2011)

Design thinking

(Carlgren et al.,

2016)

Anticipation Early establishment of central assumptions Problem framing Yes ./. Yes Yes

Reaction Continuous and rapid experimentation to test

assumptions

Prototyping as test Yes Yes Yes Yes

Anticipation Use of prototypes as instruments for communication

and assessment

Prototyping as communication Yes Yes Yes Yes

Anticipation Early user integration through prototype tests and

other assessment techniques

User integration Yes Yes Yes Yes

Reaction Development of alternative and overlapping

prototypes throughout the FEI

Product iteration ./. Yes Yes Yes

Anticipation Early evaluation of market potential, pricing, and

implementation costs

Commercial learning ./. ./. ./. ./.

Reaction Development of alternative and overlapping business

models

Business model iteration ./. ./. Yes ./.

./.: It is used as an indicator of the absence of this factor in the referenced article.

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toward potential users and offering a tangible interface to

identify potential constraints and opportunities. In addition,

one aspect not explicitly mentioned by any of the traditional

approaches refers to (iv) early evaluation of market poten-

tial, implementation costs, and pricing scope: This element

of RVT derives from the need to include commercial consid-

erations early in the process to anticipate potential economic

success over the entire product life cycle (Verganti, 1999).

The ability to make estimations of market potential, imple-

mentation costs, and pricing scope also rests on the capability

of the firm to transfer knowledge between projects (Elmquist

& Le Masson, 2009).

Central mechanisms relating to reacting capabilities are,

according to Verganti (1999), overlapped development ac-

tivities and redundancies. The corresponding RVT elements

include (v) continuous and rapid experimentation to test as-

sumptions and (vi) the development of alternative and over-

lapping prototypes which take place throughout the whole

duration of the FEI. Together, the continuous experimen-

tation and solution iteration accelerate learning and reduc-

ing uncertainty through overlapping trial- and- error cycles.

Furthermore (vii) the development of alternative and over-

lapping business models ensures to find the optimal approach

for value creation, delivery, and capture early in the process.

This early and continuous validation of information reduces

the need for costly corrective actions at later stages (Verganti,

1997) with respect to the product/service as well as the busi-

ness model.

This conceptualization of RVT provides a unique set of

activities that extend prior FEI practices in order to realize

planned flexibility.

2.2

RVT and its performance relevance

While research on the relevance of the front- end phase of in-

novation processes is not scarce and has produced valuable

knowledge, a number of issues remain to be explored. In par-

ticular, this includes the question of which activities actually

take place and to what degree they need to be planned and

formalized (Dziallas & Blind, 2019; Eling & Herstatt, 2017;

Reid & de Brentani, 2004; Zhang et al., 2019). The relevance

of this issue becomes clear when considering that decisions

made at the front- end phase of innovation processes have been

shown to have a considerable impact on the performance of

the innovation process (Cooper & Kleinschmidt, 1986; Eling

et al., 2014; Florén et al., 2018; Khurana & Rosenthal, 1998).

The concept of RVT with its set of activities might provide

an answer to this call for guidance in the FEI.

To link RVT with innovation performance and taking into

consideration fuzziness as the major challenge of the FEI

(Khurana & Rosenthal, 1998), we take an organizational in-

formation processing view. The lack of clarity in the FEI can

be traced down to both external as well as internal uncertainty

and equivocality (Daft & Lengel, 1986; Winkler et al., 2015).

Equivocality is rooted in the complex nature of innovation

processes (Salomo et al., 2007) while uncertainty emerges

from the inherent need of organizations as social systems to

process information (Mackenzie, 1984). Uncertainty or the

lack of sufficient information necessary to perform a specific

task (Galbraith, 1967; Souder et al., 1998) can stem, in the

context of innovation projects, from competitive market envi-

ronments, information asymmetries among departments, and

from technological developments (Tushman & Nadler, 1978;

Zhang et al., 2019). Equivocality, on the other hand, refers to

the simultaneous existence of conflicting information about a

situation in projects and the lack of clarity on the cause– effect

relationships (Daft & Lengel, 1986). In the context at hand,

equivocality can arise from unclear customer expectations,

unclear supplier involvement, conflicting frames of reference

of the departments involved in projects (Dougherty, 1992),

and unexpected technological developments (Reid & de

Brentani, 2004; Zhang et al., 2019). Therefore, information

processing to systematically reduce uncertainty and equivo-

cality over the course of innovation projects is assumed to be

key to success.

Following organizational information processing theory,

gathering, interpreting, and synthetizing information within

organizations tend to follow specific models that allow for

efficient processes and effective information processing.

This happens mostly through the establishment of plans and

standards that structure how an organization gathers and pro-

cesses information (Tushman & Nadler, 1978). The capabil-

ity to revisit existing and gather new knowledge in order to

ensure the alignment of an emerging product or service con-

cept with customer needs and expectations is of particular

relevance at the FEI. In this context, RVT offers a way to

establish such a model for information gathering and process-

ing. Our reasoning behind the assumption of RVT as leading

to higher performance of innovation projects rests on the fol-

lowing arguments:

2.2.1

Quality of results

One of the main, if not the central, outcome of innovation

projects in the front end of innovation is the development of

a robust concept definition (Florén et al., 2018) that can be

developed into a feasible product or service with clear profit

potential (Dziallas & Blind, 2019; Florén et al., 2018; Kim &

Wilemon, 2002a; Seidel, 2007; Verganti, 1999). As such, the

key activities during this phase concern acquiring informa-

tion to reduce uncertainty and processing of information to

address equivocality. Together, these activities should lead

to more robust concept definitions (Daft & Lengel, 1986;

Verworn, 2009; Zhang et al., 2019).

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RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

Early user integration through prototypes and other as-

sessment techniques expands the amount of information

available on user needs and the need- solution fit, which

contributes to the refinement of concepts in terms of qual-

ity (Bogers & Horst, 2014; Carlgren et al., 2016; Cui & Wu,

2017; Elsen et al., 2012; Hassi & Laakso, 2011; Highsmith,

2009; Thomke, 1998; von Hippel & Katz, 2002). Repeated

and overlapping iterations of the concept alleviate ambiguity

around concept goals, which should help increasing the prob-

ability of achieving quality goals (Bhattacharya et al., 1998).

Last, the development of alternative and overlapping proto-

types as well as business models builds a knowledge base

on which efficient decision- making, in terms of the choice

of the concept to pursue, can draw on. Over the course of

an innovation project, this knowledge supports the genera-

tion of new opportunities not initially considered and facil-

itates taking into consideration, early in the process, further

aspects of the business model that go beyond the product/

service concept itself (BenMahmoud- Jouini & Midler, 2020;

Cui & Wu, 2017; Highsmith, 2009; Ries, 2011; Savoia, 2019;

Täuscher & Abdelkafi, 2017; Thomke, 1998; von Hippel &

Katz, 2002). The RVT elements support learning, early in

the project, about the actual customer needs, which concept

caters best to their needs and technical requirements, and

which business model to use for value creation, delivery, and

capture, increasing the likelihood that projects following the

RVT approach likely arrive at a robust high- quality product

and business concept.

2.2.2

Development time

Early user involvement contributes to rapidly examining and

validating concepts and thereby reduces implementation

time (Calantone et al., 2003; Huchzermeier & Loch, 2001).

Similarly, the early procurement of information through ex-

perimentation and prototyping can contribute to anticipate

problems further down the project, avoiding time delays

(Roth et al., 2020; Tatikonda & Montoya- Weiss, 2001), and

contributing to meeting project time goals. Communication

and alignment between functional departments through the

early establishment of central assumptions and prototypes

helps establish a common understanding of and consensus

on the concept and its implications, thus reducing uncer-

tainty and avoiding lengthy implementation time (Kim &

Wilemon, 2002b). Thus, the RVT elements accelerate the

development of a robust concept early in the project by

gathering information and feedback from both custom-

ers and internal stakeholders and by aligning all involved

departments on the market, technological, service, and

production- related matters already when the project is still

in the FEI.

2.2.3

Development costs

Overall, activities contributing to the exhaustiveness in the

procurement of information on potential sources of uncer-

tainty are vital to direct flexibility to the areas in which it

is needed, avoiding high costs typically related to high lev-

els of flexibility (Huchzermeier & Loch, 2001). Gathering

user- related information through prototypes can contribute

to save costs further down the project life cycle by estab-

lishing the solution- needs fit in the very early stage of con-

ceptualization (Brown, 2008; Roth et al., 2020). Through

prototyping and the early estimation of implementation costs

and commercial aspects, uncertainties about product deliv-

erables can be anticipated and addressed early on, avoiding

costly changes in the downstream activities in the innovation

process (Calantone et al., 2003; Cooper & Sommer, 2016;

Liedtka, 2017; Roth et al., 2020). Thus, the RVT approach

allows the project to achieve an early and validated freezing

point for the concept that is not subject to costly change in

later implementation stages of the project such as redefin-

ing product specifications or architecture due to overlooked

manufacturing restrictions.

Following the presented arguments and the tenets of

planned flexibility, we assume RVT to have a positive effect

on innovation program performance (Jissink et al., 2019;

Schultz et al., 2013). Organizations implementing and de-

ploying the concept of RVT broadly across its innovation

projects are thus assumed to cope better with reducing the un-

certainty and equivocality inherent in this innovation phase

resulting in its innovation outputs to be more likely to deliver

superior quality on time and within budget.

Hypothesis 1 The use intensity of an RVT approach at the

front end of innovation processes has a positive impact

on innovation program performance.

2.3

The RVT– performance relation: A

contingency perspective

As noted earlier, past research on approaches implementing

elements of planned flexibility was mainly analyzed in case

studies and very particular contexts, but popular science pos-

tulates them to be universally effective to resolve the chal-

lenges of the FEI (Ries, 2011). Scholars have criticized such

implied generalizations (Elsbach & Stigliani, 2018; Liedtka,

2015; Razzouk & Shute, 2012) and have particularly empha-

sized to take contingencies into account (Nakata & Hwang,

2020; Roth et al., 2020). This coincides with the central tenet

of contingency theory (Emery & Trist, 1965; Scott, 1981)

which highlights the role of and an adequate fit between organ-

izational design and environmental factors for organizational

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performance. Organizational contingency theorists challenge

the idea of the existence of a “one- best- way” of organizing

and identify environmental uncertainty as a central factor in

the choice of organizational design (Lawrence & Lorsch,

1967, Van de Ven et al., 2013). As technologies, markets,

and the tasks organizations have to perform in them vary ac-

cording to the environment they operate in, organizations and

their subsystems need to adapt their internal structures in re-

sponse to the characteristics of said environments in order to

achieve their performance goals. (Lawrence & Lorsch, 1967,

Scott, 1981). In the context of this study, investigating the

relevance of RVT requires considering both the external and

the internal environment of the organization.

The external environment in which FEI processes take

place is often subject to rapid and unpredictable changes

(Bourgeois & Eisenhardt, 1988; Dess & Beard, 1984). The

situations brought on by these conditions have been grouped

under the concept of turbulences (Calantone et al., 2003;

Jaworski & Kohli, 1993; Li et al., 2020). A turbulent environ-

ment is understood “as one in which frequent and unpredict-

able market and/or technological advances accentuate risk

and uncertainty in the strategic planning process” at the FEI

(Calantone et al., 2003, p. 91). These conditions, then, influ-

ence the formulation of plans and forecasts (Morgan et al.,

2019), as they may cause, for instance, sudden modification

in consumer preferences (Glazer & Weiss, 1993; Homburg

et al., 2017; Jaworski & Kohli, 1993) in the case of market

turbulence, or the rapid obsolescence of technologies used

when technological turbulence is involved (Li et al., 2020;

Schultz et al., 2019). Seeing RVT as an uncertainty- reducing

approach at the FEI, it is reasonable to assume variations in

terms of the performance relevance of RVT dependent on the

level of turbulence of the external environment causing these

uncertainties.

An aspect internal to the organization that influences the

relationship between FEI activities and innovation perfor-

mance relates to the shared norms that guide both beliefs and

social behavior in an organization (Moorman, 1995; Shane,

1995). Innovation activities are embedded in the specific cul-

tural setting of the organization. Not the least due to their

relative stability, these settings become a contingency to the

performance of innovation activities (Atuahene- Gima & Ko,

2001; Calantone et al., 2003; Kleinschmidt et al., 2010).

Past research on FEI practices has mostly not taken internal

contingency factors into account (Nakata & Hwang, 2020),

which creates the problem of limited generalizability of their

effectiveness. Due to the uncertainty in the FEI and the gen-

eral risk associated with innovation activities, the perfor-

mance relevance of certain practices might also depend upon

the organization's general willingness to take risk (Nakata &

Hwang, 2020). As RVT aims to systematically reduce uncer-

tainty and risk in the FEI, it is reasonable to assume that its

efficacy might depend upon its fit to the organizational risk

propensity. Furthermore, RVT facilitates rapid trial and error

processes to learn fast, but organizations differ in their time

orientation, that is, their preferred planning horizons and

their adherence to those plans. Thus, RVT’s performance rel-

evance might also depend upon its fit to organizational time

orientation.

2.3.1

External environment

First, we suggest that the performance relevance of RVT will

be dependent upon market turbulence. Innovation activities,

aimed at achieving competitive advantage (Calantone et al.,

2010; García- Manjón & Romero- Merino, 2012; Glazer &

Weiss, 1993; Mahoney & Pandian, 1992), are inherently

linked to the markets for which the outcomes of innovation

development are intended (Atuahene- Gima, 2003; Atuahene-

Gima & Ko, 2001). Instances of changing customer needs

and expectations as well as dynamics in the competitor

structures (Atuahene- Gima, 2003; Glazer and Weiss 1993;

Homburg et al., 2017; Morgan et al., 2019) lead to varying

degrees of market turbulence (Calantone et al., 2003; Morgan

et al., 2019; Souder et al., 1998). With increasing market tur-

bulence, markets are in a state of constant change, contribut-

ing to an uncertain state of information (Atuahene- Gima &

Wei, 2011). Gathering and building on market information is

conceptualized as a fundamental element of RVT. As such,

in contexts of market turbulence, organizations might benefit

even more from RVT: Product and market- related assump-

tions need to be explicitly defined and tested early and con-

stantly in each project in order to anticipate and react timely

to changes in the environment (Christensen & Bower, 1996),

which RVT ensures. Testing these assumptions through

experimentation enables validation and procurement of in-

formation that allows for continued refinement of the innova-

tion goals (Jissink et al., 2019; Kaplan & Orlikowski, 2013;

Nakata & Hwang, 2020; Urban et al., 1996). Development

of early prototypes allows to visualize and communicate the

features of the new product or service to customers and value

chain partners, which contribute to the further establish-

ment of the validity of project assumptions (BenMahmoud-

Jouini & Midler, 2020; Menold et al., 2017; Thomke, 1998).

Establishing repeated prototyping as a regular practice con-

cerning products and business models allows to generate

knowledge to counteract the inherent uncertainty of turbulent

markets (Athuahene- Gima & Wei, 2011), react to changing

conditions, and test varying aspects of potential business

models related to the new product or service (BenMahmoud-

Jouini & Midler, 2020), thus reducing equivocality.

In sum, with increased turbulence in the market, the

relevance of timely and validated information for suc-

cess increases. Consequently, securing such informa-

tion through RVT is even more beneficial for innovation

454

RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

projects of organizations operating in turbulent environ-

ments. In contrast, stable markets entail less complex

and dynamic situations with less uncertainty, leading to

a reduced imperative for early and repeated information

search (Atuahene- Gima & Wei, 2011; Palmer & Wiseman,

1999) and testing of market- related assumptions (Morgan

et al., 2019).

Hypothesis 2 The positive relationship between the use

intensity of an RVT approach at the front end of inno-

vation processes and innovation program performance

will be stronger (weaker) with increasing (decreasing)

market turbulence.

Second, the performance relevance of RVT will also be

dependent upon technology turbulence. Organizations dif-

fer in “the rate of change associated with new […] tech-

nologies” (Calantone et al., 2010, p. 1072) which they are

confronted with. The emergence of new technologies often

implies a constant search for information on technological

changes and adjusting concepts to these changes in order to

maintain competitive advantage (von Hippel & Tyre, 1995).

For innovation projects, the risk of concept obsolescence

increases with the frequency of technological developments

(Calantone et al., 2003). In addition to this risk of obso-

lescence on the market side, dynamic technological envi-

ronments can render existing knowledge structures obsolete

(Tushman & Anderson, 1986). Gaining more robust techno-

logical knowledge through fast iterations and validation of

prototypes as fundamental elements of RVT should become

more valuable for innovation projects of organizations op-

erating in contexts of technological turbulence. In order to

react quickly to the described double risk of obsolescence,

and to increase the speed- to- market, RVT allows for the

development of multiple and overlapping design iterations

in an innovation project. This increases the probability of

incorporating state- of- the- art technology (Eisenhardt &

Tabrizi, 1995; Moorman & Miner, 1998). Constantly re-

visiting technology- related assumptions and their early val-

idation becomes increasingly relevant when technological

conditions change frequently (Morgan et al., 2019; Song

& Montoya- Weiss, 2001). Thus, we suggest that with in-

creased technological turbulence, the ability to rapidly test

and validate technological assumptions of concepts be-

comes more relevant for project success, and following the

RVT approach will be even more beneficial for innovation

programs of organizations in such environments.

Hypothesis 3 The positive relationship between the use

intensity of an RVT approach at the front end of inno-

vation processes and innovation program performance

will be stronger (weaker) with increasing (decreasing)

technology turbulence.

2.3.2

Internal environment

Organizations vary with respect to their risk propensity. While

some organizations seek risky business opportunities, others

have developed a “play- it- safe” mentality with a strong pro-

clivity for low- risk innovation activity (Antoncic & Hisrich,

2001; Das & Joshi, 2007; Shane, 1995). Innovation activities,

and FEI activities, in particular, are inherently uncertain and

thus, attitudes toward risk become a relevant facet of organi-

zational culture (Elsbach & Stigliani, 2018; Khazanchi et al.,

2007; Khurana & Rosenthal, 1998). One of the main sources

of risk is the fear of making costly, suboptimal decisions

(Mohan et al., 2017). The information collected in innova-

tion projects through early experimentation and validation of

concepts through prototyping allows for aligned, informed

decision- making, contributing to the establishment of experi-

mentation and repeated validity tests as legitimate practices

under risk- averse conditions. Furthermore, the information

made available through RVT will contribute to alleviate the

uncertainty related to innovation projects. Following contin-

gency theory (Emery & Trist, 1965; Scott, 1981), such an ad-

equate fit between a risk- averse cultural setting and RVT as

an approach to the front- end of innovation processes should

result in improved innovation performance. In addition, RVT

allows employees under risk- averse organizational cultures

to seek more innovation activities: Early testing, creating vis-

ibility and ability to communicate about the innovation facets,

and developing alternative business models at an early inno-

vation stage, makes innovation opportunities more tangible

and creates an experience of better- controlled risks (Bogers

& Horst, 2014; Mu et al., 2009; Sarooghi et al., 2015). As

risk- averse organizations have a higher need for information

in order to reduce uncertainty than risk- affine organizations

(Antoncic & Hisrich, 2001), RVT will allow even risk- averse

organizations to explore and realize more innovative oppor-

tunities (Elsbach & Stigliani, 2018; Mu et al., 2009), thus

making the performance relevance of RVT for innovation

projects likely to be greater for such risk- averse organiza-

tions as opposed to their risk- affine peers.

Hypothesis 4 The positive relationship between the use

intensity of an RVT approach at the front end of inno-

vation processes and innovation program performance

will be stronger (weaker) with increasing (decreasing)

levels of organizational risk avoidance.

Temporal orientation constitutes a further relevant facet of

organizational culture (Ofori- Dankwa & Julian, 2001; Tang

et al., 2020). It refers to the attitudes of the organization to-

ward time and the belief of the members of an organization of

being able to influence, through their actions, the long- term

future of the organization (Ruvio et al., 2014; Tang et al.,

2020). Recognizing time pressure or the lack thereof may be

455

PEÑA HÄUFLER Et AL.

shaped by different factors such as stock market listing and

resulting demands for quarterly reports, product life- cycle

dynamics, or investment horizons (Doyle & Hooley, 1992;

Laverty, 1996; Lin et al., 2019). Hence, organizational cul-

ture varies with respect to its time perspectives and how dil-

igently organizations assess long- term consequences before

taking decisions (Ruvio et al., 2014; Tang et al., 2020).

Long- term orientation as a specific configuration of tem-

poral orientation builds on the beliefs on the plasticity of the

distant future through concrete actions of the firm (Ruvio et al.,

2014). Consequently, high value is attributed to developing

and adhering to thorough plans, with the intention of impact

on distant future rather than short- term performance (Laverty,

1996; Lin et al., 2019). In contrast, RVT aims for the early and

constant generation of information over thorough deliberation

and assessment of all potential options. Quick and short- term

learning in projects might not fit well with a conservative or-

ganizational culture valuing long- term perspectives (Chandy

& Tellis, 1998). Repeated experimentation within each project

based on incomplete information or rough prototypes contrasts

with the preference for meticulous planning, comprehensive

search, and thorough deliberation of long- term consequences.

Equivocal sources of information stemming from experiment-

ing with different prototypes or overlapping business models in

projects are at odds with the equivocality- avoidant long- term

orientation (Laverty, 1996; Yadav et al., 2007). Furthermore,

the nature of RVT’s iterative, experimental activities can be

perceived as disturbing routines and thus leading to delays in

activities, which may be in conflict with productivity norms

(Elsbach & Stigliani, 2018). Such a misfit of culture and RVT

is likely to result in limited acceptance of such an approach for

innovation projects. Even if employed, the approach may be

executed with limited enthusiasm, or its results will lack legit-

imacy and are barely used for subsequent decisions, signifi-

cantly reducing its value for innovation (Elsbach & Stigliani,

2018; Rauth et al., 2014). Hence, long- term time orientation

as an organizational culture facet is suggested to weaken the

performance relevance of RVT.

Hypothesis 5 The positive relationship between the use

intensity of an RVT approach at the front- end of in-

novation development and innovation program per-

formance will be weaker (stronger) in a more (less)

long- term- oriented organizational culture.

METHODS

3.1

Data collection and sample

To test the proposed hypotheses, depicted in Figure 1, we

collected data from a cross- sectional sample of firms located

in Germany and Austria in 2016 and 2017 over a period of

18months. Executives and senior managers were contacted

by email and phone to inform them about the purpose of the

study, which covered different areas of innovation manage-

ment. The managers expressing their commitment to partic-

ipate in the study with their organizations nominated a set

of employees responsible for innovation tasks. A separate

subsection of the survey, pertaining to the firm's innovation

program performance, was sent to a manager at the executive

level, a priori identified as possessing a competent perspec-

tive on the innovation portfolio of the corresponding firm.

All nominated employees independently received an invita-

tion to an electronic survey and a reminder after 2weeks in

case they had not completed the survey so far. In total, our

final sample included responses from 1022 informants in 129

organizations (on average 7.92 informants per organization).

We summarize the sample characteristics in Table 2 on firm

FIGURE 1 Main model

Innovation program

performance

Rapid validity testing

H.1 (+)

Risk aversion Long term orientation

Market turbulence Technology turbulence

H.2 (+)H.3 (+)

H.4 (+)H.5 (–)

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RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

and informant levels. In order to assess nonresponse bias,

we compare early (first quantile) and late respondents (last

quantile) (Armstrong & Overton, 1977). None of the t- tests

performed for the main model variables result in a significant

difference between the two groups, which suggests that non-

response bias is unlikely to be an issue.

3.2

Measures and scale properties

We use multi- item measures and five- point Likert- type scales

to capture all main constructs. Where possible, we apply estab-

lished indicators applied in prior research, and the development

of new scales closely follows the corresponding literature. In

order to ensure content validity, the items were pretested with

representatives from 20 organizations in two consecutive rounds,

resulting in minor wording adaptions based on their feedback.

Innovation program performance is assessed with three

items adapted from Gemünden et al. (2007) that capture the

innovation execution success at the portfolio level within the

previous 3years following the traditional triple constraints:

achieving the intended quality objectives, being completed

on time, and being within their budget restrictions.

RVT is captured with seven items encompassing the full

conceptual domain of RVT. We draw on the conceptual work

of Verganti (1999) and the corresponding literature on par-

ticular practices described in design thinking, lean innova-

tion, pretotyping, and prototyping for the development of the

items. Our operationalization of RVT allows us to assess the

intensity of use of such an approach of planned flexibility to

cope with uncertainty and ambiguity. Elements, items, and

the supporting literature are summarized in Table 3.

Market turbulence and technology turbulence are as-

sessed with five and four items correspondingly, adapted from

TABLE 2 Sample characteristics

Firm size (FTE) No.Percentage Firm size (revenue; EUR) No.Percentage

Less than 100 FTE 31 24.0% Less than 50Mio. 35 27.1%

101– 250 35 27.1% 51– 250Mio. 38 29.5%

251– 500 21 16.3% 251– 500Mio. 13 10.1%

More than 500 FTE 42 32.6% more than 500Mio. 26 20.2%

n.a. 0 0.0% n.a. 17 13.2%

Industry No.Percentage

Manufacturing goods (chemicals, food, plastics, glass, etc.) 52 40.3%

Industrial engineering (machine construction, plant engineering,

etc.)

18 14.0%

Utilities (energy, water, recycling) 42 32.6%

Others (information technology, industrial

research)

17 13.2%

No. informants No.Percentage Job areas (informants) No.Percentage

2– 3 informants 21 16.3% R&D/Innovation

management

219 21.4%

4– 5 18 14.0% Marketing/Sales 158 15.5%

6– 7 37 28.7% Leadership/Strategy 146 14.3%

8– 9 22 17.1% Production 86 8.4%

more than 10 informants 31 24.0% Product management 79 7.7%

Project management 44 4.3%

Hierarchical position

(informants)

No.Percentage Quality management 20 2.0%

Upper management 162 15.9% Purchasing 20 2.0%

Middle management 220 21.5% IT 17 1.7%

Lower management/team leader 340 33.3% Controlling/accounting 16 1.6%

Employee 256 25.0% Human resources 11 1.1%

n.a. 44 4.3% others 101 9.9%

n.a. 105 10.3%

Total number of informants 1022

Total number of firms 129 Average no. informants by the firm 7,92

457

PEÑA HÄUFLER Et AL.

Venkatraman (1989) and Calantone et al. (2003) that capture

whether the organizational environment is characterized by

rapidly changing customer requirements, fast shifts in the com-

petitive landscape, and frequent technological breakthroughs.

Risk aversion of the organization is assessed with three

items following Jaworski and Kohli (1993) that capture the

organization's tendency to adopt a play- it- safe and “wait-

and- see” posture when it comes to innovation activities and

decisions.

Long- term orientation captured with three items adopted

from Ruvio et al. (2014) the organization's tendency to take a

long- term perspective as opposed to only considering short-

term profits in decision- making about innovation activities.

The survey includes several control variables. Literature

provides strong evidence for the success of innovation activi-

ties to be dependent upon the level of formal control (Cooper,

1990; Schultz et al., 2013). Therefore, we include innovation

process formality (the degree to which all innovation activ-

ities of the firm follow clearly defined stages and decision

points) with four items from Schultz et al. (2019) and project

management control (the degree to which all projects have

clear goals that are closely monitored) with four items from

Schultz et al. (2013). Dummy variables represent industry

differences (goods manufacturer, industrial engineering,

utilities, and a residual group of other industries) as innova-

tion practices and their effectiveness might vary by industry

(Morgan et al., 2019). Furthermore, the number of employ-

ees is used as a proxy for organization size, as it may influ-

ence the levels of formalization (Atuahene- Gima et al., 2005;

Damanpour, 1996; Hall et al., 1967; Schultz et al., 2019). By

recoding the absolute size variable into six categories, we

avoid biases caused by extreme outliers.

Common method variance issues are addressed by fol-

lowing recent recommendations (Chang et al., 2010; Kline

et al., 2000; Podsakoff et al., 2003). Respondents were in-

formed about the confidentiality of their responses and asked

to answer honestly. Fact- based items reduce biases caused by

social desirability and anchor effects. Furthermore, respon-

dents were asked about aspects of innovation management

not related to the investigated concepts and rated a set of

other innovation outcomes, which helps covering the actual

focus of this study. This makes it unlikely that respondents

bias the results with their theories- in- use. Ex post, Harman's

single factor test including all items of the eight main model

variables is applied. Eight factors with eigenvalues >1 are

extracted, which together explained 80.4% of the variance,

whereas the largest factor accounts for only 20.9%. Thus,

common method bias is unlikely to be present in the used

data set.

With the phenomenon and constructs investigated in this

research being located at the organizational level of analy-

sis, the variables, which were assessed by several informants

within each organization, are aggregated on the organiza-

tional level by calculating the mean across the individual

responses. Therefore, we apply the referent- shift consensus

composition model (Chan, 1998). The items are phrased

in such a way that informants did not assess their activities

and perceptions but those of their organization as a whole

by shifting the referent of the content in the items from the

self to the organization. Specifying the organization as the

referent rather than the individual is crucial, as the referent

shift ensures that the practices in the entire organization are

assessed, even if the individual does not apply the investi-

gated practices as opposed to most others in the organization.

TABLE 3 Rapid validity testing scale elements and supporting research

RVT items RVT labels Supporting literature (selected)

When carrying out innovation activities, we form central assumptions

at an early stage, which we then test and refine.

Problem framing Riess (2011); Carlgren et al. (2016); Cui

and Wu (2017); Savoia (2019)

We continuously experiment during the product/service development

phase in order to test our assumptions thoroughly.

Prototyping as test Riess (2011); Bogers and Horst (2014);

Carlgren et al. (2016); Cui and Wu

(2017); Savoia (2019)

We already begin to develop prototypes during an early development

phase in order to visualize, communicate, and assess our concepts.

Prototyping as

communication

Riess (2011); Bogers and Horst (2014);

Carlgren et al. (2016); Cui and Wu

(2017); Savoia (2019)

We carry out systematic prototype tests, for example, systematic

customer survey and customer observation.

User integration Riess (2011); Bogers and Horst (2014);

Carlgren et al. (2016); Cui and Wu

(2017); Savoia (2019)

Over the course of developing the product/service, we produce several

prototypes from mock- ups through to functional models.

Product iteration Carlgren et al. (2016); Cui and Wu (2017);

Savoia (2019); Bogers and Horst (2014)

Using prototypes, we already attempt to estimate market potential

as well as the production costs and pricing scope of our new

products/services.

Commercial learning Verganti (1997, 1999)

We experiment with different business models, for example,

developing alternative business cases.

Business model

iteration

Ries (2011)

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RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

Within- group consensus is used to justify the aggregation of

the individuals’ collective perceptions to represent the con-

struct score of the higher organizational level. Statistically,

this is assessed with the intraclass correlation coefficient ICC

(1, k) informing about the interrater reliability and agreement

(LeBreton & Senter, 2008; Shrout & Fleiss, 1979). The val-

ues ranged between 0.69 and 0.92 and indicate high interrater

agreement for all constructs. The value for long- term orien-

tation (0.51) also indicates sufficient, but lower within- group

consensus compared with the other constructs. This culture

facet appears in some cases to be perceived with some vari-

ation. However, the aggregation is still valid as the overall

score indicates the diffusion of the long- term orientation in

the organization.

To test the scale properties, we conduct further tests to

assess their validity and reliability. Cronbach's alpha coeffi-

cients are all >0.77 for all multi- item measures, supporting

their internal consistency (Hair et al., 2006). Principal com-

ponent analysis (varimax rotation) extracts only one factor

with an eigenvalue >1 for each construct and loadings >0.72

for all items, which demonstrates unidimensionality (Ahire

& Devaraj, 2001). Confirmatory factor analysis including all

multi- item measures is applied to assess convergent validity.

All factor loadings were >0.50 and significant (p < 0.001).

The average variance extracted of all variables is >0.54, and

the composite reliability values are >0.70. Discriminant

validity is demonstrated by the square root of the average

variance extracted of all variables being larger than their cor-

relations with any other construct (Fornell & Larcker, 1981).

The global fit indices are also within the recommended

boundaries (Hair et al., 2006). For the model including all

predictor variables, the comparative fit index is 0.913, the

root mean square error of approximation is 0.082, and the

χ2/d.f. ratio is 1.854. When adding the dependent variable,

the model also shows acceptable fit: the comparative fit index

was 0.893, the root mean square error of approximation is

0.085, and the χ2/d.f. ratio is 1.916. Means, standard devia-

tions, correlations, Cronbach's alpha, ICC (1, k), and average

variance extracted are summarized in Table 4. The scales are

reported in the Appendix Table A1.

RESULTS

The hypotheses are tested using ordinary least- square regres-

sion analysis. The results are summarized in Table 5. The

baseline model with the covariates (Model 1) shows that risk

aversion (β = – 0.20, p < 0.05) has a negative impact on in-

novation program performance and project management con-

trol positively affects performance (β = 0.39, p < 0.01).

When adding RVT (Model 2), the additional predictor has

a significant positive effect on innovation program perfor-

mance (β = 0.28, p < 0.05), in support of Hypothesis 1. In

total, the predictors explain 17% of the variance in innovation

program performance, which constitutes an increase of 3%

compared to the baseline model.

To test the remaining moderation hypotheses, we mean-

center the moderator and independent variables to facilitate

the interpretation of coefficients (Aiken & West, 1991).

Table 5 shows the unstandardized coefficients of the step-

wise regression, with innovation program performance as

the dependent variable and one moderation effect per model.

The results of Model 3 show that market turbulence does

not moderate the relationship between RVT and innovation

program performance (β = 0.01, p = n.s.). This leads us to

reject Hypothesis 2. Model 4 assesses the moderating effect

of the technological turbulence of the organization's environ-

ment. The positive performance impact of RVT is strength-

ened when technological turbulence increased (β = 0.24, p

< 0.01), which lends support to Hypothesis 3. The model

including the moderator increases the variance explained by

5% compared with the main model (Model 2). In Model 5, an

increase in the organization's risk- aversion also strengthens

the positive performance impact of RVT (β = 0.21, p < 0.05),

in support of Hypothesis 4. The explained variance in the de-

pendent variable increases by 4% when the moderation term

is added to the model. Model 6shows that a stronger long-

term orientation hampers the positive performance impact of

RVT (β = – 0.31, p < 0.001), supporting Hypothesis 5. The

moderated model explains 8% of additional variance in the

dependent variable compared with the main model.

The plots of simple slope analyses are depicted in Figure 2

and illustrate the strength of RVT’s effect on innovation pro-

gram performance for low (mean minus one standard devia-

tion) and high (mean plus one standard deviation) levels of all

investigated moderators. In addition, we assess the significance

of each simple slope (Aiken & West, 1991). With respect to

the moderator market turbulence, the gradient for low (0.20, t

= 1.12; p = 0.27) and for high (0.23, t = 1.39; p = 0.17) levels

of market turbulence is not significant. For technology turbu-

lence, the gradient is only significant for high levels (0.53, t =

3.36; p = 0.001) but not for low levels (– 0.06, t = – 0.39; p =

0.70). Similarly, the gradient for high levels of risk aversion is

significant (0.48, t = 3.06; p = 0.003) but not for low levels

(0.09, t = 0.77; p = 0.45). The gradient for low levels of long-

term orientation is significant (0.87, t = 3.99; p < 0.001) but

not for high levels (– 0.22, t = – 1.35; p = 0.18).

DISCUSSION

For organizations to cope with the uncertainties and equivo-

cality in the FEI, scholars have suggested iterative learning

and development in form of approaches like design thinking,

lean innovation, pretotyping, and prototyping. Despite their

popularity in practice, these approaches subsume different

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PEÑA HÄUFLER Et AL.

TABLE 4 Mean, standard deviations, and correlation matrixa

Mean SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

ICC (1,

k) AVE

1. Industry dummy (utility) (— ) (— ) (— ) (— ) (— )

2. Industry dummy

(manufacturing)

(— ) (— ) (— ) (— ) (— ) (— )

3. Industry dummy (engineering) (— ) (— ) (— ) (— ) (— ) (— ) (— )

4. Firm size (FTE) 3.88 1.42 – 0.08 0.20*– 0.04 (— ) (— ) (— )

5. Market turbulence 3.01 0.49 0.55*** – 0.41*** – 0.27** – 0.04 (0.79) 0.69 0.54

6. Technology turbulence 2.72 0.57 – 0.02 – 0.23** 0.04 0.09 0.45*** (0.88) 0.76 0.65

7. Risk aversion 3.14 0.66 0.30*** – 0.12 – 0.07 0.18*0.11 – 0.19*(0.91) 0.74 0.77

8. Long- term orientation 3.60 0.46 0.31*** – 0.15 – 0.16 – 0.10 0.14 – 0.07 – 0.14 (0.77) 0.51 0.56

9. Innovation process formality 2.64 1.27 – 0.63*** 0.60*** 0.09 0.39*** – 0.43*** – 0.11 0.00 – 0.13 (0.98) 0.92 0.94

10. Project management control 2.66 0.75 – 0.44*** 0.46*** 0.09 0.34*** – 0.40*** – 0.14 – 0.08 – 0.01 0.76*** (0.94) 0.79 0.87

11. Rapid validity testing 2.88 0.72 – 0.58*** 0.48*** 0.19*0.26** – 0.32*** 0.20*– 0.31*** – 0.16 0.64*** 0.62*** (0.93) 0.79 0.70

12. Innovation program

performance

3.12 0.56 – 0.01 0.05 0.00 – 0.05 – 0.12 – 0.15 – 0.20*0.14 0.04 0.22*0.18*(0.81) 0.64 0.87

Note: n = 129.

aS.D., standard deviation. Cronbach's alpha was reported along the diagonal (in italics). ICC (1, k) intra- class correlation coefficient. AVE average variance extracted.

*p < 0.05,; **p < 0.01,; ***p < 0.001 (two- tailed).

(— ) is meant to reflect that there were no mean standard deviations and cronbach's alpha scores to report, due to the fact that these were binary values and single item constructs.

460

RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

TABLE 5 Effects on innovation program performancea

Dependent variable:

Innovation program

performance Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Variables β B S.E. p β B S.E. pβBS.E. p β B S.E. p β B S.E. p β B S.E. p

Intercept (— )*** 3.42 0.73 0.000 (— )*** 3.08 0.74 0.000 (— )*** 3.10 0.77 0.000 (— )*** 2.94 0.72 0.000 (— )*** 2.80 0.74 0.000 (— )*** 2.68 0.72 0.000

Industry dummy (utility) 0.07 0.09 0.20 0.660 0.06 0.07 0.19 0.714 0.07 0.08 0.20 0.700 0.15 0.17 0.19 0.364 0.14 0.17 0.19 0.393 0.05 0.06 0.18 0.732

Industry dummy

(manufacturing)

– 0.02 – 0.02 0.18 0.904 – 0.11 – 0.12 0.18 0.503 – 0.11 – 0.12 0.18 0.503 – 0.09 – 0.10 0.18 0.581 – 0.04 – 0.05 0.18 0.780 – 0.07 – 0.08 0.17 0.658

Industry dummy

(engineering)

0.00 – 0.01 0.20 0.972 – 0.06 – 0.10 0.20 0.610 – 0.06 – 0.10 0.20 0.614 – 0.07 – 0.11 0.19 0.568 – 0.03 – 0.05 0.20 0.815 – 0.08 – 0.12 0.19 0.517

Firm size (FTE) – 0.04 – 0.02 0.04 0.675 – 0.05 – 0.02 0.04 0.635 – 0.05 – 0.02 0.04 0.633 – 0.06 – 0.03 0.04 0.503 – 0.04 – 0.01 0.04 0.698 – 0.05 – 0.02 0.04 0.591

Market turbulence – 0.02 – 0.02 0.15 0.900 .000 0.00 0.15 0.991 – 0.01 – 0.01 0.16 0.957 – 0.11 – 0.12 0.15 0.415 – 0.04 – 0.04 0.14 0.775 0.00 0.00 0.14 0.973

Technology turbulence – 0.14 – 0.14 0.11 0.203 – 0.23 – 0.23 0.12 0.055 – 0.23 – 0.23 0.12 0.058 – 0.16 – 0.16 0.12 0.179 – 0.18 – 0.18 0.12 0.138 – 0.21 – 0.21 0.11 0.071

Risk aversion – 0.20*– 0.17 0.09 0.048 – 0.15 – 0.13 0.09 0.149 – 0.15 – 0.13 0.09 0.149 – 0.08 – 0.07 0.09 0.420 – 0.11 – 0.09 0.09 0.285 – 0.12 – 0.10 0.08 0.212

Long- term orientation 0.05 0.06 0.12 0.626 0.06 0.08 0.11 0.511 0.06 0.07 0.12 0.522 0.07 0.09 0.11 0.436 0.06 0.08 0.11 0.495 0.13 0.16 0.11 0.151

Innovation process

formality

– 0.19 – 0.09 0.08 0.256 – 0.26 – 0.11 0.08 0.136 – 0.25 – 0.11 0.08 0.138 – 0.20 – 0.09 0.07 0.234 – 0.33 – 0.15 0.08 0.055 – 0.08 – 0.04 0.08 0.637

Project management

control

0.38** 0.28 0.10 0.007 0.29*0.22 0.11 0.041 0.29*0.22 0.11 0.041 0.26 0.19 0.10 0.067 0.28*0.21 0.100 0.043 0.14 0.11 0.11 0.314

Rapid validity testing 0.28*0.22 0.11 .049 0.28 0.22 0.11 .052 0.31*0.24 0.11 0.028 0.37*0.28 0.11 0.012 0.29*0.22 0.10 0.034

Market turbulence × Rapid

validity testing

0.01 0.02 0.13 0.902

Technology turbulence ×

Rapid validity testing

0.24** 0.29 0.11 0.008

Risk aversion × Rapid

validity testing

0.21*0.19 0.08 0.023

Long- term orientation ×

Rapid validity testing

– 0.31*** – 0.45 0.13 0.001

R20.14 0.17 0.17 0.22 0.21 0.25

Adj. R20.07 0.10 0.09 0.14 0.13 0.17

ΔR20.14 0.03 0.00 0.05 0.04 0.08

F2.00*2.22*2.02*2.75** 2.55** 3.22***

ΔF2.00*3.94*0.02 7.23** 5.28*11.89***

Note: n = 129.

aβ, standardized beta coefficient; B, unstandardized beta coefficient; S.E., standard error; p, level of significance; (Adj.) R2, (adjusted) explained variance.

*p < 0.05,; **p < 0.01,; ***p < 0.001 (two- tailed).

461

PEÑA HÄUFLER Et AL.

activities under their umbrella terms and might lack certain

elements necessary to enact planned flexibility in the FEI.

Furthermore, there is still a lack of empirical evidence about

the performance relevance of these integrated approaches,

mostly relying on normative assumptions or anecdotal evi-

dence (Elsbach & Stigliani, 2018; Liedtka, 2015; Razzouk &

Shute, 2012). Together, this makes it difficult to determine

which activities enable planned flexibility in the FEI and if

investing in building this capability actually pays off. With

this research, we aim to contribute to this stream of the in-

novation literature by conceptualizing and thereby building

a better understanding of what elements constitute a com-

prehensive approach enabling planned flexibility and by

providing empirical evidence of its relevance for innovation

performance.

Motivated by this initial situation, we set out in this study

to conceptualize an approach referred to as RVT based on

considerations of Verganti’s (1999) concept of planned flex-

ibility. Its comprehensive set of seven defining elements ag-

gregate what is proposed by the practice- oriented approaches

mentioned above and extends it by introducing commercial

learning, that is, the early evaluation of market potential,

pricing, and evaluation costs as a further activity at the FEI.

We thereby contribute to the FEI literature by providing a

comprehensive set of activities to balance anticipation and

reaction capabilities and thus enable planned flexibility. We

FIGURE 2 Plots of moderation effects

462

RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

introduce a concept that includes and goes beyond what has

been part of existing approaches. As such, the RVT concept

shows, which elements, enabling rapid learning and devel-

opment in the FEI, are currently not present in popular ap-

proaches and thereby highlights areas for improvement for

future revisions of these approaches. Building on the frame-

work of planned flexibility to determine its relevant elements,

RVT also offers a conceptual fundament, as opposed to the

normative argumentation often observed in prior approaches

such as in the heralded “pretotyping manifestos” (Savoia,

2019), design thinking (Brown, 2008), and lean innovation

(Blank, 2013).

We further hypothesize that organizations implementing

RVT will achieve higher innovation program performance,

that is, that their innovation projects are more likely to

achieve their goals on time within budget. The elements of

RVT facilitate iterative gathering and the use of information

collected from multiple stakeholders to arrive at clear and

high- quality concept definitions, alignment between depart-

ments to reduce delays, and anticipate potential challenges to

avoid costly changes later in the innovation process or product

life cycle. Drawing on multirespondent data collected from a

cross- sectional sample of 129 organizations, we find support

for this proposed positive relationship. This finding is an im-

portant extension of the FEI literature: With few exceptions,

for example (Roth et al., 2020), prior empirical evidence of

the effectiveness of popular approaches such as design think-

ing, pretotyping, and lean innovation stems from anecdotes

or case- study data. Using a quantitative study design, this

research shows that organizations implementing RVT as an

overarching concept including the aspects covered by prior

approaches, also report higher levels of performance across

their innovation program. Thus, we provide stronger empiri-

cal evidence of the performance relevance of approaches fa-

cilitating planned flexibility in the FEI.

Following prior recommendations to take contingency

factors into consideration when studying such approaches to

learn more about the generalizability of their effectiveness

(Nakata & Hwang, 2020), we also investigated the role of rel-

evant environmental factors so far neglected. The results are

encouraging and suggest future research on the contingent

effectiveness of different FEI approaches enabling planned

flexibility. Considering the role of the external environment

as an important driver of uncertainty and equivocality in the

FEI, we examined the role of technological and market tur-

bulence. A fast- changing technology landscape implies the

emergence of different options for technologies involved in

the development and use of new products or service con-

cepts. In these situations, quick testing of assumed opportu-

nities becomes more relevant, to sort out the most promising

alternatives (Thomke, 1998). Hence, RVT allows to reduce

ambiguity and to select technologies, which receive better

response from the market (Calantone et al., 2003). The data

supported our assumption that organizations confronted with

higher technological turbulence benefit more from RVT.

Thereby, the concept of RVT relates to the literature about

technological breakthroughs that highlighted the threats of

detrimental technology path dependencies of organizations

(Vergne & Durand, 2010) and the increased uncertainties

coming along with highly innovative technologies that can

cause organizations to ignore opportunities despite their up-

side potentials (Jalonen, 2012). Scholars suggest organiza-

tions to develop abilities to engage in iterative learning cycles

(Buganza et al., 2009), to probe early user reaction to radical

innovation (Lynn et al., 1996), and deliberately setting out to

test alternative and new business models (Hu, 2014). RVT in-

tegrates and complements these proposed abilities and can be

seen as a comprehensive approach that increases the chances

to cope with uncertainties inherent to technological dynamics

and to leverage the innovation upsides of such dynamics to a

better degree.

We assumed RVT to be more relevant for firms in tur-

bulent markets, as it facilitates the reduction of uncertainty

regarding customer needs, needs- solution fit, competitive

advantage, and optimal business model. Contrary to expec-

tations, the data did not support the supposed moderation

effect. Rather, RVT seems to be positively related to perfor-

mance independent of market turbulence levels. One reason

could lie in the assumption that the positive effect of imple-

mentation of RVT is independent of market turbulence and

thus organizations in stable market environments can equally

profit from it. A further explanation for the lack of support

for this hypothesis can stem from the applied performance

measure captures the internal aspect of performance, and that

the moderation effect might only become visible with respect

to market- related performance aspects such as customer

satisfaction, revenue growth, and competitive advantage. It

might be that organizations in highly turbulent markets have

no higher immanent benefit from clearer concept definitions

and adhering to time and budget constraints as opposed to

their peers in less turbulent market environments. However,

they could obtain more benefit from RVT in later stages

when the product or service launches by providing solutions

and business models that fit better with customer needs and

the competitive landscape at this very moment in the rapidly

changing market.

With respect to internal factors, we find support that orga-

nizations with a rather risk- averse posture benefit more from

RVT than their risk- affine peers. Thus, organizations charac-

terized by a culture, which tries to avoid risk as much as possi-

ble, could overcome their risk of inertia by engaging in RVT.

In line with the values of these organizations, RVT offers a

path to reduce risks and uncertainty to an acceptable level

by introducing a planned approach to experimentation at the

FEI. Without quick systematic tests of assumptions, seeking

early market input, and exploring alternative business models

463

PEÑA HÄUFLER Et AL.

offered by RVT, risk- averse organizations will unlikely per-

form well in innovation because no approach reduces un-

certainty inherent in innovation that fits their play- it- safe

mentality (Rodríguez et al., 2008).

Furthermore, we hypothesize that RVT with its constant

information flows and iterations does not fit well organiza-

tions with a long- term orientation, which emphasizes me-

ticulous planning ahead for longer periods and adhering to

those plans. The data support this assumption, and it seems

that RVT outputs lack legitimacy in such cultural settings

and thereby fail to produce the intended performance impact.

Whereas prior research has neglected such internal contin-

gency factors when investigating the relevance of different

approaches to master the challenges of the FEI, this study

demonstrates that cultural aspects play an important role.

MANAGERIAL IMPLICATIONS

This research provides several implications for practition-

ers. First, we provide evidence that organizations benefit

from the broad implementation of RVT in their FEI activi-

ties. Particularly, organizations in industries characterized by

high technological turbulence, in which technologies change

constantly and are characterized by frequent technologi-

cal breakthroughs that even challenge established business

models in the industry, investments into building RVT ca-

pabilities seem promising to ensure that innovation activi-

ties deliver as promised on time within budget. Anticipating

customer's needs and expectations through early integration

and the use of prototypes and other interaction techniques

helps ensure need- solution fit and reduces implementation

time by rapidly procuring information to examine and vali-

date concepts, potentially preventing costly changes further

along the implementation process. Reacting to changing and/

or unexpected customer feedback by rapidly iterating pro-

totypes support in reducing ambiguity around the features

of the concept, contributing to increased concept quality.

Problems can be anticipated through experimentation and

prototyping, which can contribute to avoiding delays in ex-

ecution time. Keeping within project time frames is also sup-

ported by results of experiments and prototypes, inasmuch

that they can be used to generate a common understanding of

the concept under development, ensuring alignment among

internal stakeholders. RVT activities also involve business

modeling and commercial learning, which prior popular ap-

proaches have barely, or not at all, considered. Managers are

recommended to include the architecture of value creation,

delivery, and capture as well as the early evaluation of mar-

ket potential, pricing, and implementation costs early on in

the FEI popular in practice offers a significant further activ-

ity. Integrating this enriches the understanding of feasibility

and potential returns of the ideas developed and provides a

further argument for managers to consider in FEI implemen-

tation decisions.

In organizations that have not applied any rapid learn-

ing and development principles before, introducing popular

methods such as lean innovation or design thinking is cer-

tainly a good starting point. Therefore, managers can make

use of the popularity of said approaches to get investing

decision- makers and applying employees to buy in. However,

since the defining elements included in popular practices are

broader than those of RVT, managers need to ensure that they

complement them with further practices. This also applies

to organizations in which one of the discussed approaches

is already established. For instance, design thinking should

be complemented by practices that support the early evalu-

ation of market potential and implementation costs, assess

technological aspects, and iterate on business model de-

signs. Otherwise, FEI activities remain limited to ensuring

the customer needs- solution fit through customer integration,

experimentation, and prototyping but neglect the technical,

economic, and commercial aspects of rapid concept genera-

tion and validation. Rather than focusing on particular pop-

ular approaches, managers are recommended to implement

practices that together cover all RVT elements when design-

ing the FEI to achieve maximum performance impact.

RVT practices are of particular value for organizations

with a stronger posture toward risk avoidance. Especially

managers in large established organizations often find

themselves in a context which tends to rely more on well-

known routines and technologies rather than entrepreneurial

opportunity seeking and new technology exploration, and

thereby struggle to realize innovation and renewal (Ganco

& Agarwal, 2009; O'Connor & DeMartino, 2006; Sandberg

& Aarikka- Stenroos, 2014). This should speak especially to

managers in risk- averse sectors like utilities (Kearney et al.,

2009; Tremml, 2019), including firms in the electricity,

water, sewage service, and natural gas business. RVT can be

seen and should be framed as an approach in the FEI to iden-

tify and actually overcome such problems: Applying RVT as

a concept to reflect on the firm's position toward risk offers

a valuable opportunity to assess which of its elements can

be strategically deployed to reduce uncertainty and thus ad-

dress risk- avoidant attitudes in innovation programs. RVT, as

a planned and controllable approach to innovation that fo-

cuses on the rapid reduction of uncertainty and risk inherent

in innovation initiatives, can contribute to alleviate con-

straints like tighter controls for resource utilization faced by

managers in risk- averse industries (Kearney et al., 2009). The

iterative process with multiple prototypes in search of the op-

timal technological approach together with the integration of

customers to test usability and acceptance ensure that stable,

validated concepts are available once the decision for further

investments into downstream activities is made, thus provid-

ing managers with validated evidence on the feasibility of the

464

RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

newly developed concepts for further implementation. The

early consideration and validation of commercial as well as

business model aspects allow for better- informed decisions

about whether to pursue FEI outcomes further. Thus, RVT

particularly fits the cultural mindset of risk- averse organiza-

tions. Furthermore, adopting and deploying RVT might pro-

vide an avenue for risk- averse organizations to establish an

innovation- friendly culture by legitimating flexibility- related

practices through their application and validation (Elsbach &

Stigliani, 2018). This potential of RVT to support cultural

changes is particularly relevant for contexts in which risk-

aversity seems to impede exploiting the competence of orga-

nizations in the core businesses (Tremml, 2019).

However, managers need to be aware that if their orga-

nization is characterized by a strong long- term orientation,

RVT might not be as effective. The idea of RVT to collect

data and act on it on a continuous basis goes against the

preference of long- term planning and sequential rather than

overlapping and experimental approaches. Managers in such

organizations need to be aware that if they implement RVT

in their organizations, this approach, as well as its outcomes,

might find less acceptance among employees and decision-

makers. This might require them to tighten their monitoring

efforts and management support for innovation activities to

create the commitment and motivation among employees to

follow RVT principles. Furthermore, the investment into es-

tablishing RVT in the FEI as well as getting further funding

to pursue outcomes of RVT- driven FEI activities might also

require managers to engage in more issue selling and promo-

tion activities to convince organizational decision- makers of

the merits of the approach and its outcomes.

LIMITATIONS AND FUTURE

RESEARCH

This study has some limitations, which should be noted

and can inform future research. With respect to the selected

performance metric, we used a project portfolio- based per-

formance measure that captured the extent to which the pro-

jects of the innovation program meet their quality, time, and

budget objectives. Thereby, we followed prior recommenda-

tions to take the project life cycle into account when select-

ing appropriate performance metrics (Shenhar et al., 2001)

and selected this internal performance indicator as opposed

to financial or market success- related performance metrics.

A similar approach has been performed in one of the rare

quantitative studies on the effectiveness of design thinking

(Roth et al., 2020) in which project performance metrics like

budget, time, and quality are seen as being closely linked to

the activities conducted at the FEI (Tatikonda & Rosenthal,

2000). The internal success of projects as an immanent out-

come relates more closely to the concept of RVT in the FEI

than a market or financial performance. The latter perfor-

mance dimensions can also be impacted by the proficiency

of downstream activities such as launch and sales activities

or postlaunch moves of competitors. That being said, pro-

ject success metrics are neither fully decoupled from market

characteristics nor overall innovation program performance

(Kock & Gemünden, 2019). Faster changing customer needs

can trigger to change project requirements and thereby af-

fect the time and budget necessary to adapt to the changed

requirements. The same applies to moves of competitors or

changes in value chain partners (Brettel et al., 2012; Hauser

et al., 2006). Managerial measures that improve internal

performance are likely to also affect economic- and market-

related performance. This is also supported by the findings

like internal project performance metrics being positively as-

sociated with performance indicators such as customer satis-

faction, commercial success, and profitability (e.g., Cooper

& Kleinschmidt, 1995; Shenhar et al., 2001). Nevertheless,

future research might investigate the economic performance

relevance of RVT at the market level and thereby provide

clear evidence to this still unanswered question.

Furthermore, our intention was to conceptualize and as-

sess the effectiveness of RVT as a comprehensive approach

drawing on the principles of planned flexibility (Verganti,

1997, 1999) and aggregating the different elements pro-

posed by popular FEI practices design thinking, lean inno-

vation, pretotyping, and prototyping. We find support for our

proposition that an organizational implementation of RVT is

associated with innovation program performance. Future re-

search, however, might further investigate the relative impor-

tance of each defining element of RVT for success. However,

this might require changing the level of analysis to the indi-

vidual project to appropriately consider project characteris-

tics that are likely to make some elements of RVT to matter

more than others for project performance. For instance, there

is reason to believe that the relative performance relevance of

experimentation and prototyping is higher for projects with

higher degrees of innovativeness as past research on radical

innovation projects has suggested (e.g., Mascitelli, 2000).

Furthermore, explicit user integration might be of higher

relative performance relevance in product innovation proj-

ects as opposed to service innovation projects. Services are

created in close interaction together with the customer (e.g.,

Storey et al., 2016) and thereby user integration is an integral

part of service development, whereas product development

can more easily omit close user integration. Thereby, prod-

uct innovation projects might benefit relatively more from

user integration as it is less naturally embedded in the de-

velopment process. Another interesting extension from this

research would be the analysis of the relative importance

of RVT elements in product versus process innovation. The

RVT concept can also be applied to process innovations, and

it would be interesting to see if elements such as (internal)

465

PEÑA HÄUFLER Et AL.

user integration, commercial learning, or prototyping differ

between product and process project contexts with respect to

their relative performance relevance.

Finally, the exploration of further contingency factors

might be of high value. We provide support for our initial

assumption that the effectiveness of RVT depends upon var-

ious environmental factors. In this study, we focused on ex-

ternal factors that are causing more or less uncertainty and

equivocality in the FEI in form of market and technologi-

cal turbulence that RVT actually aims to reduce. Future re-

search might inquire further into this industry perspective.

One promising approach would be to investigate whether the

application of RVT differs between firms operating in manu-

facturing or the service business. For instance, and due to the

involvement of customers, employees, and network partners,

frontline employees often responsible for service innovation,

and the higher customization of services to customer needs,

service innovation is more complex (Gallouj & Weinstein,

1997; Storey et al., 2016) and requires a higher proficiency

in managing internal and external information flows (Kang

& Kang, 2014). Past research finds that firms with a stron-

ger emphasis on the provision of services benefit even more

from better market knowledge, which depends upon the pro-

ficiency of managing information flows (Kroh et al., 2018).

RVT might thereby be even more effective in firms with a

stronger service focus as its elements are directed toward fa-

cilitating knowledge gathering and diffusion between inter-

nal and external stakeholders.

Internally, we focused on contingency factors that aimed

to compensate for the tendency of past practices such as de-

sign thinking or lean innovation to the origin and having been

investigated in entrepreneurial and small business contexts

when investigating the generalizability of the performance

relevance of RVT. However, further factors of the internal

environment might be of relevance. One relevant area is the

fit between the experimental, iterative approach of RVT and

the level of formal control of projects and innovation activ-

ities. With the data at hand, we performed an additional as-

sessment, not reported explicitly in the results section, and

included interaction terms of RVT with innovation process

formality and project management control. Both interaction

terms (project management control × RVT: β = 0.061, B =

0.055, S.E. = 0.096; innovation process formalization × RVT:

β = 0.098, B = 0.146, S.E. = 0.068), indicating that RVT

does not conflict with the formal controls an organization ap-

plies to manage its innovation activities. This leads us to the

suggestion to rather focus on further aspects of organizational

culture and orientation that might make RVT more or less

effective. For instance, the level by which an organization is

offensive versus defensive in its response to external threats

prefers a rather analytical versus improvised approach to in-

formation generation and knowledge building, or has a pro-

active versus reactive stand for opportunity- seeking (Morgan

& Strong, 2003; Talke, 2007). Following contingency theory,

the fit of RVT might vary according to these organizational

mindsets and thereby also differ in their effectiveness in these

different internal environments.

ACKNOWLEDGMENT

Open access funding enabled and organized by ProjektDEAL.

CONFLICT OF INTEREST

The authors have read and agreed to the Committee on

Publication Ethics (COPE) international standards for

authors.

ETHICS STATEMENT

The authors have read and agreed to the Committee on

Publication Ethics (COPE) international standards for authors.

ORCID

Birgit Peña Häufler https://orcid.org/0000-0001-8205-8721

Dietfried Globocnik https://orcid.org/0000-0001-9934-7933

Søren Salomo https://orcid.org/0000-0002-2578-3262

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How to cite this article: Peña Häufler, Birgit,

Globocnik, Dietfried, Landaeta Saldías, Paola, and

Salomo, Søren. 2021. "Rapid Validity Testing at the

Front End of Innovation." Journal of Product

Innovation Management 38: 447– 472. https://doi.

org/10.1111/jpim.12585

AUTHOR BIOGRAPHIES

Dr. Birgit Peña Häufler is a postdoctoral re-

searcher at the Chair of Technology and Innovation

Management at Technische Universität Berlin. She

holds a graduate degree in social sciences from the

University of Bonn and a doctorate in social and

economic sciences from the Technische Universität

Berlin. Her research centers around individual cre-

ativity and early stages of organizational innova-

tion and has been presented in international con-

ferences like Innovation and Product Development

Management Conference and European Congress of

Psychology.

Dr. Dietfried Globocnik works as a senior scientist

at the Alpen- Adria Universität and the University of

Graz. He holds a doctorate in social and economic

sciences from the University of Graz and a habilita-

tion in business administration from the Alpen- Adria

Universität. His research interest entails innovation

marketing, corporate entrepreneurship, and orga-

nizing innovation activities in MNEs. His academic

work is published in books and journals, such as

the Journal of Product Innovation Management,

Technovation, and European Management Journal.

Ms. Paola Landaeta Saldías, M.Sc., is a research

fellow at the Chair of Technology and Innovation

Management at the Technische Universität Berlin.

She holds a graduate degree in commercial engi-

neering from the University of Talca, Chile. In her

doctoral research, she focuses on innovation manage-

ment practices in Latin America with a focus on for-

malization and digitization of innovation processes.

Prof. Dr. Søren Salomo holds the Chair of

Technology and Innovation Management at the

Technische Universität Berlin. He holds a diploma

and a doctorate in business administration from

Kiel University. His research interests entail corpo-

rate innovation management with a special focus on

process and organizational system mechanisms for

supporting radical innovation. His work is published

in journals, such as the Journal of Engineering and

Technology Management, Creativity and Innovation

Management, and Journal of Product Innovation

Management.

471

PEÑA HÄUFLER Et AL.

APPENDIX

TABLE A1 Measures

Construct/Source Items

Innovation program performance (1 = strongly disagree, 5 = strongly agree)

The quality of results met our expectations

Source: Gemünden et al. (2007) The planned development times were achieved.

The planned development budgets were kept.

Rapid validity testing (1 = strongly disagree, 5 = strongly agree)

Conceptually rooted in Verganti (1999), see Table

3 for details.

When carrying out innovation activities, we form central assumptions at an early stage

which we then test and refine.

We continuously experiment during the product/service development phase in order to

test our assumptions thoroughly.

We already begin to develop prototypes during an early development phase in order to

visualize, communicate, and assess our concepts.

We carry out systematic prototype tests, for example, systematic customer surveys and

customer observation.

Over the course of developing the product/service, we produce several prototypes, from

mock- ups through to functional models.

Using prototypes, we already attempt to estimate market potential as well as the

production costs and pricing scope of our new products/services.

We experiment with different business models, for example, developing alternative

business cases.

Market turbulence (1 = strongly disagree, 5 = strongly agree)

Adapted from Calantone et al. (2003) and

Venkatraman (1989)

Many new competitors are active in the market.

The competitive conditions in the market are unpredictable.

Customers’ needs in our industry are changing rapidly.

Many new value chain partners (suppliers, service partners) are active in the market.

Business models often change in the market.

Technology turbulence (1 = strongly disagree, 5 = strongly agree)

Adapted from Calantone et al. (2003) and

Venkatraman (1989)

Our industry often experiences technological breakthroughs.

The technologies applied in our industry are constantly changing.

Technologies from different technological fields are often combined in our industry.

New technologies in our industry often trigger business model changes.

Risk aversion (1 = strongly disagree, 5 = strongly agree)

Adapted from Jaworski and Kohli (1993) Our company is characterized by an “always play- it- safe” mentality.

With respect to innovation, we have a wait- and- see posture.

We have a strong proclivity for low- risk innovation activity.

Long- term orientation (1 = strongly disagree, 5 = strongly agree)

Adapted from Ruvio et al. (2014) Our innovation decisions explicitly take long- term and future developments into

consideration.

When taking decisions, we also always consider the future consequences for our

company.

We value long- term success over short- term profits.

472

RAPID VALIDITY TESTING AT THE FRONT END OF INNOVATION

Construct/Source Items

Innovation process formality (1 = strongly disagree, 5 = strongly agree)

Source: Schultz et al. (2019) Our company uses a formal innovation process, for example, a standardized set of stages

and go/no- go decisions that guide all innovation activities from the idea through to

market launch.

Our standardized innovation process lists and defines specific activities for each phase

of the process (e.g., the validation stage contains activities such as prototype and

customer tests).

Our standardized innovation process includes clearly defined go/no- go decision points

for each stage of the process.

Our standardized innovation process defines “gate keepers,” whose task is, for example,

to review the activities at each stage of the process as well as decide on whether to

continue or abort the project.

Project management control (1 = strongly disagree, 5 = strongly agree)

Source: Schultz et al. (2013) Our company has clear, written, and measurable goals for its innovation projects.

Specific financial goals are defined for our innovation projects.

The progress of our innovation projects and the achievement of innovation goals are

regularly evaluated.

We have defined procedures for evaluating our innovation projects.

All innovation projects, even unsuccessful projects, are regularly evaluated in order to

learn from experience.

We monitor the performance of our innovation projects at a defined time after market

introduction.

TABLE A1 Continued