Configurations of Innovations across Domains: An ... · neels, 2002; Sidhu et al., 2007). However, most of the literature focuses on technology, leaving “rather little explicit

Configurations of Innovations across Domains:

An Organizational Ambidexterity View*Feng Zhang, Yonggui Wang*, Dahui Li, and Victor Cui

How do firms balance explorative and exploitative innovation for superior firm performance? While most prior

studies have approached this issue by focusing on technology-related innovation, the role of balancing exploration

and exploitation in other important organizational domains, i.e., marketing, and the interaction effect of ambidex-

terity across different domains have been overlooked. This study contributes to this line of research by investigating

how firms simultaneously balance exploration and exploitation across two critical domains, namely technology

innovation and market innovation. The study distinguishes four types of configurations: market leveraging (technol-

ogy exploration and market exploitation), technology leveraging (technology exploitation and market exploration),

pure exploitation (technology exploitation and market exploitation), and pure exploration (technology exploration

and market exploration). From an organizational ambidexterity perspective, the current work investigates whether

and how these different combinations exert distinctive effects on firm performance. Specifically, the article posits

that (a) technology exploration and market exploitation complement each other, and (b) technology exploitation

and market exploration also complement each other, such that both market leveraging and technology leveraging

strategies have positive effects on firm performance. The article also maintains that such positive relationships are

fully mediated by differentiation and low cost advantages. Conversely, it is argued that (c) technology exploration

and market exploration conflict with each other, and (d) so do technology exploitation and market exploitation,

such that both pure exploration and pure exploitation have negative effects on firm performance. Hypotheses were

tested using survey data collected from 292 manufacturing and service firms in China. The results supported most

of the hypotheses, except that pure exploration demonstrated no significant relationship with firm performance.

Practitioner Points

� In the Chinese context, complementary exploration

and exploitation in technology and market domains

benefit firm performance, while pure exploitative

strategy in both domains damages firm performance.

� Market leveraging strategy suits large firms with suf-

ficient resources for expensive R&D investment,

which can develop innovative products and enhance

its competitive advantages in existing markets.

� Technology leveraging strategy works for small

firms with limited resources for R&D investment,

which can apply existing technologies to new mar-

kets that have been overlooked by large rivals.

� Firms should manage their innovation process to

balance the positive effect of product differentiation

and the negative effect of costs and risks incurred in

innovation on firm performance.

Introduction

Innovation can drive competitive advantages and

achieve superior performance in competitive mar-

ket environments (Damanpour, 1991; Zou, Fang,

and Zhao, 2003), but successful innovations remain

challenging for firms. Recent studies reveal the impor-

tance of both technology-related innovation, which

refers to the adoption of improved or new technologies

in new product development processes, and market-

related innovation, which involves new ways of

serving existing or emerging customers (e.g., Dan-

neels, 2002; Day and Moorman, 2010; O’Reilly and

Tushman, 2008; Sidhu, Commandeur, and Volberda,

2007; Voss and Voss, 2013). While customer needs

and demands motivate firms to develop new offerings,

the supply of technologies enables firms to provide

Address correspondence to: Yonggui Wang, School of Business,University of International Business and Economics, No. 10 HuixinDongjie, Chaoyang District, Beijing 100029, China. E-mail: [email protected]. Tel: 86-10-64493509.

*This research was supported in part by National Natural ScienceFoundation of China (Grant No. 12&ZD205, 71302005), Social ScienceFoundation of Beijing (Grant No. 15JDJGA044) and Collaborative Inno-vation Center for China Economy.

J PROD INNOV MANAG 2017;34(6):821–841VC 2016 Product Development & Management AssociationDOI: 10.1111/jpim.12362

new attributes in these offerings (Danneels, 2002).

However, if these demand and supply sides of innova-

tions cannot be linked, a firm is unlikely to succeed

(Danneels, 2002). This is an especially critical dilem-

ma for firms with scarce or constrained resources.

Innovation also depends on exploration and exploi-

tation processes (Atuahene-Gima, 2005; He and Wong,

2004; Jansen, Van Den Bosch, and Volberda, 2006).

Refining and extending current resources may enhance

a firm’s efficiency and short-term performance (March,

1991), but a sole focus on such exploitation processes

can create competence traps and prevent organizational

changes (Levitt and March, 1988). Searching for and

experimenting with new alternatives can foster longer-

term innovations (March, 1991), though an over-

whelming focus on exploration can initiate an endless

search cycle, unrewarding changes, and a high risk of

failure (Levinthal and March, 1993; Volberda and

Lewin, 2003). Thus, balancing exploration and exploi-

tation represents another difficult dilemma (Gupta,

Smith, and Shalley, 2006). Virtually all firms struggle

to manage these two types of dilemmas.

Accordingly, there is a clear need for simultaneous

and balanced views of both technology versus market

(Day and Moorman, 2010; O’Cass, Heirati, and Ngo,

2014) and exploitation versus exploration (Raisch, Bir-

kinshaw, Probst, and Tushman, 2009; Voss and Voss,

2013) dilemmas. Previous studies suggest that both

technology- and market-related innovations can have

positive impacts on business performance (Aspara,

Tikkanen, P€ontiskoski, and J€arvensivu, 2011; Dan-

neels, 2002; Sidhu et al., 2007). However, most of the

literature focuses on technology, leaving “rather little

explicit attention” devoted to the market or the rela-

tionship between these two complementary innovation

activities (Aspara et al., 2011; Sidhu et al., 2007).

Similarly, with regard to the trade-off between exploi-

tation and exploration, the empirical findings are

mixed (e.g., Atuahene-Gima, 2005; Gibson and Birkin-

shaw, 2004; Gupta et al. 2006; He and Wong, 2004;

Raisch and Birkinshaw, 2008; Volberda and Lewin,

2003; Voss and Voss, 2013), likely because of the

challenges associated with balancing these two com-

plementary but contradictory activities. Exploitation

and exploration have distinct requirements for struc-

tures, routines, and managerial behaviors, such that

they compete for scarce resources and can produce

organizational tension (Gupta et al., 2006; He and

Wong, 2004).

To address these challenges, prior research suggests

ambidexterity within a specific domain (Lavie, Kang,

and Rosenkopf, 2011; Voss and Voss, 2013),1 such as

technology innovation (He and Wong, 2004), marketing

management (Vorhies, Orr, and Bush, 2011), and quality

management (Zhang, Linderman, and Schroeder, 2012).

But this stream of literature neglects the possibilities and

potential benefits of ambidexterity across domains and

does not clarify why or how ambidexterity leads to

superior performance. Therefore, this article adopts the

configuration theory and posits that firm performance

depends on combinations of organizational elements

(Siggelkow, 2002). This article also extends organization-

al ambidexterity theory to classify the dimensions of

technology- or market-related innovation (e.g., O’Cass

et al., 2014; Voss and Voss, 2013). By combining these

two theories, this article develops specific technology–

market configurations and describes their benefits and

deficiencies according to the ability to achieve ambidex-

terity across multiple domains (Lavie and Rosenkopf,

2006; Lavie et al., 2011). With this novel approach,

this article explains how to achieve technology–market

synergy and suggests a new route to organizational

ambidexterity.

BIOGRAPHICAL SKETCHES

Dr. Feng Zhang (Ph.D., Nankai University) is an associate professor at

Nankai University in China. His research focuses on innovation, strate-

gy, and organizational studies in China. He has published his research

in several major Chinese journals. He is an editorial board member of

European Management Journal.

Dr. Yonggui Wang (Ph.D., City University of Hong Kong) is a profes-

sor of marketing and Dean of Business School at University of Interna-

tional Business and Economics in China. His current research is in

service management, value co-creation, CRM, and customer innova-

tions. He has published papers in Journal of Marketing, Journal of

Operations Management, Journal of Management, and so on.

Dr. Dahui Li (Ph.D., Texas Tech University) is a professor of MIS at

the University of Minnesota Duluth. His research focuses on technolo-

gy innovation and business-to-business relationships. He has published

in Decision Support Systems, Information & Management, Journal of

the Association for Information Systems, and elsewhere.

Dr. Victor Cui (Ph.D., University of British Columbia) is assistant pro-

fessor in business strategy at the Asper School of Business, University

of Manitoba. His research focuses on inter-firm competition and alli-

ance and technological innovation. His research has appeared in Stra-

tegic Management Journal.

1In this context, a “domain” refers to a specific business function or activity. For

example, Voss and Voss (2013, p. 1459) refer to product and market domains as

“two most basic business functions,” and Lavie and Rosenkopf (2006) define three

domains according to their function, structure, and attribute. Lavie et al. (2011)

explore the benefits of organizational ambidexterity across function and structure

domains, which they define as “a discrete field of organizational activity.” This

article considers technology- and market-related functions or activities as two dis-

tinct domains.

822 J PROD INNOV MANAG2017;34(6):821–841

F. ZHANG ET AL.

This study makes several contributions. First, unlike

prior research that focuses primarily on technology-

related innovations (Aspara et al., 2011; Sidhu et al.,

2007), this study explains how to configure technolo-

gy- and market-related innovations in order to lessen

the tensions between the two innovations. In addition,

this article distinguishes exploration from exploitation

in both technology- and market-related innovations to

deepen understanding of their configurations. The

importance of feasible configurations for product inno-

vation is confirmed and indirect effects of different

configuration strategies are revealed.

Second, this study contributes to organizational

ambidexterity research by studying the effects of an

exploration–exploitation balance across different

domains. Different from prior studies that discuss

ambidexterity within a single domain (e.g., He and

Wong, 2004; Vorhies et al., 2011; Zhang et al., 2012),

this article investigates the impacts of exploration and

exploitation across the domains of technology- and

market-related innovations. A novel approach is

offered in order to resolve extant controversies about

the effects of organizational ambidexterity (Raisch and

Birkinshaw, 2008). This approach reflects Lavie and

Rosenkopf’s (2006) argument that firms might be able

to coordinate exploration and exploitation across dif-

ferent organizational areas.

Third, this article examines the effects of organiza-

tional ambidexterity in a new context (i.e., an emerg-

ing market). Most studies are conducted in Western

settings that are characterized with stable institutional

environments and sufficient market resources (e.g.,

Fang, Palmatier, and Grewal, 2011; Voss and Voss,

2013). However, the complexities of organizational

ambidexterity may be particularly problematic in an

emerging market (such as China) (Marquis and Qian,

2014), which is featured by inefficient legal enforce-

ment, turbulent institutional environments, and restrict-

ed access to market resources (Li and Atuahene-Gima,

2001; Li and Zhang, 2007; Sheng, Zhou, and Li,

2011). The negative effects of pure exploration or

exploitation in a single domain have been noted in the

emerging market (e.g., Gupta et al., 2006; Volberda

and Lewin, 2003), including high expropriation risks

(Li and Atuahene-Gima, 2001), chronic resource short-

ages (Sheth, 2011), and substantial dynamism (Zhou

and Poppo, 2010). By applying the view of ambidex-

terity across domains in an emerging market setting,

this study provides different evidence about the effects

of pure exploitation or exploration across domains (see

Voss and Voss, 2013).

Fourth, this study reveals how suitable configura-

tion strategies exert positive effects on firm perfor-

mance. Unlike studies that examine only the direct

effects of organizational ambidexterity, this article

responds to the persistent calls to provide more

detailed and deeper investigation (e.g., Raisch and Bir-

kinshaw, 2008). The study explores the indirect effects

of different configurations across different domains by

applying the source–positional advantages–perfor-

mance framework proposed by Day and Wensley

(1988). This framework is adopted because it posits

that a firm could attain positional advantages when

particular value-adding activities are performed at a

lower cost or in a unique way (Day and Wensley,

1988). Prior studies suggest that different configura-

tions represent a firm’s strategic orientation and efforts

to orchestrate two crucial value-adding activities,

namely, technology- and market-related innovation

(Aspara et al., 2011; Danneels, 2002). These configu-

rations could effectively motivate the drivers of posi-

tional advantages, such as efficiency, learning, or the

linkage among different activities (Day and Wensley,

1988), using the two approaches of exploration and

exploitation. The framework offers a theoretical base

for us to reveal the path through which configurations

lead to superior firm performance. In so doing, this

study offers a more fine-grained understanding of the

link between organizational ambidexterity and perfor-

mance and helps reconcile some mixed prior findings.

Theoretical Background and Hypotheses

The current work differs from prior relevant studies

about technology-market or similar links (see Table 1

for a comparison of this study with selected literature).

For example, Danneels (2002) classifies four kinds of

product innovations by configuring technology- and

customer-related competences but does not explore

these configurations’ impacts on firm performance.

Fang et al. (2011) validates a link between customer-

and technology-related assets in reference to static

resources, not the leverage or deployment of resources.

Organizational Ambidexterity and Configuration

Strategies

The concepts of exploration and exploitation appear

broadly in prior studies (Atuahene-Gima, 2005; Gibson

and Birkinshaw, 2004; He and Wong, 2004; Jansen

et al., 2006; Tushman and O’Reilly, 1996). Exploration

CONFIGURATIONS OF INNOVATIONS ACROSS DOMAINS J PROD INNOV MANAG2017;34(6):821–841

823

Ta

ble

1.

Co

mp

ari

son

of

Stu

die

s

Lit

erat

ure

Indep

enden

tvar

iable

s

Dep

enden

t

var

iable

sO

ther

var

iable

sR

esea

rch

met

hod

Res

earc

hfo

cus

Fin

din

gs

Conte

xt

Dan

nee

ls(2

002)

Cust

om

erco

mpet

ence

Tec

hnolo

gy

com

pet

ence

Ren

ewal

of

a

firm

Pro

duct

innovat

ion

types

,

explo

itat

ion

and

explo

rati

on

lear

nin

g,

etc.

Qual

itat

ive:

case

study

Pro

duct

innovat

ion

and

firm

com

pet

ence

s

New

pro

duct

sar

ecr

eate

dby

linkin

gco

mpet

ence

s

rela

ting

tote

chnolo

gie

s

and

cust

om

ers;

Som

e

uniq

ue

nat

ure

and

chal

lenges

of

dif

fere

nt

types

of

pro

duct

innovat

ion

Dev

eloped

econom

y(fi

ve

hig

h-t

ech

firm

s

inU

nit

ed

Sta

tes)

He

and

Wong

(2004)

Ex

plo

itat

ive

innovat

ion

stra

tegy

Ex

plo

rati

ve

innovat

ion

stra

tegy

Sal

esgro

wth

rate

Med

iato

rs

(not

hypoth

esiz

edan

dnot

for

ambid

exte

rity

and

its

impac

t)

Innovat

ion

per

form

ance

No

moder

ators

Em

pir

ical

:

surv

ey

Tec

hnolo

gic

al

innovat

ion

Inte

ract

ion

bet

wee

n

explo

itat

ive

and

explo

rati

ve

innovat

ion

stra

tegie

s!

sale

sgro

wth

rate

(1);

rela

tive

imbal

ance

bet

wee

n

explo

itat

ive

and

explo

rati

ve

innovat

ion

stra

tegie

s!

sale

sgro

wth

rate

(2)

Dev

elopin

g

econom

y

(man

ufa

cturi

ng

firm

sfr

om

Sin

gap

ore

and

Mal

aysi

a)

Gib

son

and

Bir

kin

shaw

(2004)

Conte

xtu

alfe

ature

s:

Per

form

ance

man

agem

ent

and

soci

alco

nte

xt

Busi

nes

sunit

per

form

ance

Med

iato

rs:

ambid

exte

rity

No

moder

ators

Em

pir

ical

:

surv

ey

Am

bid

exte

rity

inth

e

conte

xt

of

alig

nm

ent

and

adap

tabil

ity

Cap

acit

yto

sim

ult

aneo

usl

y

achie

ve

alig

nm

ent

and

adap

tabi

lity!

perf

orm

ance

(1)

Am

bid

exte

rity

full

y

med

iate

sth

ere

lati

onsh

ip

bet

wee

nco

nte

xt

and

busi

nes

s-unit

per

form

ance

Dev

eloped

and

dev

elopin

g

econom

ies

(Jap

an,

Unit

ed

Sta

tes,

Can

ada,

Fra

nce

,In

dia

,

South

Kore

a)

Lubat

kin

,

Sim

sek,

Lin

g,

and

Vei

ga

(2006)

Beh

avio

ral

inte

gra

tion

of

TM

Ts

Rel

ativ

e

per

form

ance

Med

iato

rs:

ambid

extr

ous

ori

enta

tion

No

moder

ators

Em

pir

ical

:

surv

ey

Ante

ceden

tsan

d

conse

quen

ceof

Am

bid

exte

rity

Join

tpurs

uit

of

an

explo

itat

ive

and

expl

orat

ory

ori

enta

tion!

per

form

ance

(1);

ambi

dext

erit

y

ori

enta

tion

med

iate

sth

e

rela

tion

ship

betw

een

beh

avio

ral

inte

grat

ion

of

TM

Ts

and

rela

tive

per

form

ance

Dev

eloped

econom

y

(sm

all-

and

med

ium

-siz

ed

ente

rpri

ses

from

New

Engla

nd)

Ven

kat

ram

an,

Lee

,an

dIy

er

(2007)

Sim

ult

aneo

us

ambid

exte

rity

Seq

uen

tial

ambid

exte

rity

Sal

egro

wth

Moder

ators

:fi

rmag

e;F

irm

dom

inan

ce;

deg

ree

of

mult

imar

ket

com

pet

itio

n

Em

pir

ical

:

seco

ndar

ydat

a

Inco

rpora

ting

tim

ein

toth

e

conce

ptu

aliz

atio

n

of

ambid

exte

rity

in

pro

duct

launch

es

Am

bid

exte

rity!

firm

per

form

ance

(1)

(not

signifi

cant

for

sim

ult

aneo

us

ambid

exte

rity

);m

oder

atin

g

effe

cts

wit

h

sequen

tial

ambid

exte

rity

Glo

bal

(1005

soft

war

efi

rms)


F. ZHANG ET AL.

Ta

ble

1.

Co

nti

nu

ed

Lit

erat

ure

Indep

enden

tvar

iable

s

Dep

enden

t

var

iable

sO

ther

var

iable

sR

esea

rch

met

hod

Res

earc

hfo

cus

Fin

din

gs

Conte

xt

Fan

get

al.

(2011)

Innovat

ion/c

ust

om

eras

set

dep

th

Innovat

ion/c

ust

om

eras

set

bre

adth

Per

form

ance

and

its

var

iabil

ity

Moder

ators

:in

dust

ry

dynam

ism

;

No

med

iato

rs

Em

pir

ical

:

seco

ndar

yan

d

surv

eydat

a

Sto

ckof

reso

urc

es

(sta

tic)

:in

novat

ion/

cust

om

eras

set

Dee

pin

novat

ion-b

road

cust

om

eras

set

confi

gura

tion!

per

form

ance

(1);

Dee

p

cust

om

er-b

road

innovat

ion

asse

tco

nfi

gura

tion!

per

form

ance

(1)

Dev

eloped

econom

y

(hig

h-t

ech

indust

ries

in

Unit

edS

tate

s)

Voss

and

Voss

(2013)

Pro

duct

/mar

ket

explo

rati

on

Pro

duct

/mar

ket

explo

itat

ion

Rev

enue

Moder

ators

:fi

rmsi

ze;

firm

age;

no

med

iato

rs

Em

pir

ical

:

obje

ctiv

ean

d

surv

eydat

a

Str

ateg

icco

mbin

atio

ns

of

explo

rati

on

and

explo

itat

ion,

and

per

form

ance

Pro

duct

explo

itat

ion

3

mar

ket

explo

rati

on/

explo

itat

ion)!

reven

ue

(1);

pro

duct

explo

rati

on

3m

arket

explo

rati

on!

reven

ue

(1);

pro

duct

explo

rati

on

3m

arket

explo

itat

ion!

reven

ue

(not

signifi

cant)

Dev

eloped

econom

y

(Sm

all

and

Med

ium

-Siz

ed

Ente

rpri

ses

in

Unit

edS

tate

s)

O’C

ass

etal

.

(2014)

Ex

plo

rato

ryst

rate

gy

Ex

plo

itat

ive

stra

tegy

New

pro

duct

per

form

ance

Med

iato

rs:

explo

rato

ry

pro

duct

innovat

ion,

mar

ket

ing,

and

thei

r

inte

gra

tion;

Explo

itat

ive

pro

duct

innovat

ion,

mar

ket

ing,

and

thei

r

inte

gra

tion;

No

moder

ators

Em

pir

ical

:

surv

ey

new

pro

duct

dev

elopm

ent

(NP

D)

Explo

rato

ryst

rate

gy!

explo

rato

rym

arket

ing/

explo

rato

rypro

duct

innovat

ion/a

nd

thei

r

inte

gra

tion!

new

pro

duct

dif

fere

nti

atio

n

(1);

Explo

itat

ive

stra

tegy

!ex

plo

itat

ive

mar

ket

ing/

explo

itat

ive

pro

duct

innovat

ion

and

thei

r

inte

gra

tion!

new

pro

duct

cost

effi

cien

cy

(1)

Dev

elopin

g

econom

y

(tec

hnolo

gy-

inte

nsi

ve

indust

rial

firm

s

inIr

an)

This

study

Explo

rati

ve

tech

nolo

gy

innovat

ion

Ex

plo

rati

ve

mar

ket

innovat

ion

Ex

plo

itat

ive

tech

nolo

gy

innovat

ion

Ex

plo

itat

ive

mar

ket

innovat

ion

Fir

m per

form

ance

Med

iato

rs:

dif

fere

nti

atio

n

advan

tage;

Low

cost

advan

tage;

No

moder

ators

Em

pir

ical

:

surv

ey

Res

ourc

esle

ver

age

acro

ssdom

ains

for

super

ior

per

form

ance

,an

d

the

med

iati

on

effe

cts

Explo

rati

ve

tech

nolo

gy

3

explo

itat

ive

mar

ket!

dif

fere

nti

atio

n(1

)/lo

w

cost

(1)!

per

form

ance

(1);

Explo

itat

ive

tech

nolo

gy

3ex

plo

rati

ve

mar

ket!

dif

fere

nti

atio

n

(1)/

low

cost

(1)!

per

form

ance

(1);

explo

itat

ive

tech

nolo

gy

3

explo

itat

ive

mar

ket!

per

form

ance

(2);

Explo

rati

ve

tech

nolo

gy

3

explo

rati

ve

mar

ket!

per

form

ance

(not

signifi

cant)

Dev

elopin

g

econom

y

(man

ufa

cturi

ng

and

serv

ice

indust

ries

in

Chin

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siti

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825

refers to the search for new alternatives; exploitation

implies the refinement of current resources or capabili-

ties (March, 1991). Researchers also recognize the

importance of balancing these two seemingly contradic-

tory activities (Raisch and Birkinshaw, 2008). Tushman

and O’Reilly (1996) propose resolving this critical

dilemma with organizational ambidexterity, which is

the capability of simultaneously exploiting existing

competencies and exploring new opportunities (Raisch

et al., 2009). However, it is difficult to achieve ambi-

dexterity because both exploration and exploitation

require purposeful effort, scarce resources, and conflict-

ing organizational routines and managerial behaviors

(Gupta et al. 2006; He and Wong, 2004). Despite some

suggestions for how to achieve ambidexterity (e.g., con-

textual, Gibson and Birkinshaw, 2004; leadership-based,

Smith and Tushman, 2005; sequential, Venkatraman

et al., 2007), firms still encounter managerial challenges

and organizational pressures, even within just a single

business domain (Gupta et al. 2006; Lavie and Rose-

nkopf, 2006; Lavie et al., 2011).

Therefore, some studies propose a domain separa-

tion logic, suggesting the pursuit of exploration in one

domain and exploitation in another (e.g., Lavie and

Rosenkopf, 2006; Lavie et al., 2011). Voss and Voss

(2013) argue that the trade-off tensions might be miti-

gated across different domains, and they demonstrate

the separation of product and market domains using

data from the United States. Implementing exploration

in technology or market domains, with exploitation in

the other, might help avoid the dispersion of marketing

resources and overcome the challenges created by con-

flicting routines and demands within domains (Lavie

and Rosenkopf, 2006). This separation might enhance

firm performance by maintaining both the novelty and

the efficiency created through ambidexterity (Lavie

et al., 2011).

Accordingly, this study proposes distinguishing

exploration and exploitation in both technology- and

market-based domains, which produces a new configu-

ration grid (Figure 1) that contains four innovation

strategies: explorative technology–exploitative market

(hereafter, market leveraging strategy), exploitative

technology–explorative market (technology leveraging

strategy), explorative technology–explorative market

(pure exploration strategy), and exploitative technolo-

gy–exploitative market (pure exploitation strategy).

Market leveraging strategy commercializes new

technologies and products to appeal to existing cus-

tomers, which should help firms maintain competitive

positions in their mainstream markets. For example,

Japan’s Seiko watch brand outperformed many Swiss

competitors and became a leader in the watch market

in the 1960s through explorative innovation of the

quartz watch. Apple also adopted this strategy and

developed completely innovative operating systems

(iOS) and software application platforms (App Store),

while still maintaining its mainstream segments. Tech-

nology leveraging strategy instead appeals to emerging

customers by improving existing technologies and

products. For example, Xiaomi, a Chinese smartphone

company, does not seek to develop any radically new

technology but rather makes pertinent improvements

to existing technologies, such as more effective pro-

duction engineering. Xiaomi also targets lower-income

customer groups that may have been neglected by

incumbent firms.

The two extreme alternatives are pure exploration

and pure exploitation. Pure exploration means search-

ing for both new technologies and new customers and

Exploitation Exploration

Pure Exploration Strategy Radical or New Technology

Emerging Market Examples: Dupont (Nylon)

Technology Leveraging Strategy Current or Mature Technology

Emerging Market Examples: XiaoMi

Market Leveraging Strategy Radical or New Technology

Existing Market Examples: Apple (iPhone)

Pure Exploitation Strategy Current or Mature Technology

Existing Market Examples: Household Appliance Manufacturers

Tech

nolo

gy

Expl

oita

tion

Expl

orat

ion

Market

Figure 1. Configurations of Technology- and Market-Related Innovations from an Organizational Ambidexterity Perspective


F. ZHANG ET AL.

developing a completely new product–market domain

(Day and Moorman, 2010). For example, after 15

years of research, DuPont famously invented nylon

and created a completely new market (i.e., plastics).

Pure exploitation instead focuses on running and rein-

forcing current products and markets (Aspara et al.,

2011), as exemplified by household appliance manu-

facturers in China. Rather than developing radical

technologies or creating new markets, these companies

invest substantially in improving operational efficiency

and reducing production costs, to persuade current cus-

tomers to buy nearly homogeneous products at lower

prices.

Configuration Strategies and Firm Performance

Firm performance depends on combinations of organi-

zational elements because a firm constitutes an organi-

zational system that is composed of highly

interdependent elements, such as activities, policies,

structural elements, resources, and their interactions

(Siggelkow, 2002). Congruent or consistent elements

benefit firm performance (Siggelkow, 2002). That is, if

the value of each element is increased in the presence

of another element (Milgrom and Roberts, 1990), a

state of fit is achieved (Siggelkow, 2002). Accordingly,

this study expands the configuration grid to propose a

conceptual framework (Figure 2) that describes how

technology- and market-based innovations might be

configured effectively to achieve superior performance.

To understand the benefits of different innovation

combinations, this article considers the interplay

among technology- and market-related activities.

The current work also adopts the theory that

describes the connections from a specific source to

positional advantages to performance (Day and Wens-

ley, 1988) to predict how different configuration strate-

gies affect firm performance. While superior skills and

resources are first suggested to be the source of posi-

tional advantages and subsequently superior perfor-

mance, later studies extend the scope of sources (e.g.,

Day and Nedungadi, 1994; Kim and Atuahene-Gima,

2010). Drawing on this framework. O’Cass et al.

(2014) develop the link from explorative and exploit-

ative product innovations to positional advantages to

explain how product innovation influences perfor-

mance. Ngo and O’Cass (2012) argue that innovation

capability could be a potential source of advantages.

This study posits that innovation configurations corre-

spond directly to the sources of positional advantages,

and these configurations determine whether technolo-

gy- and market-related activities can be performed at

low cost or in a superior way. Specifically, this study

posits that differentiation and low cost advantages,

which represent determinants of product innovation

(Kim and Atuahene-Gima, 2010; O’Cass et al., 2014),

serve as mediators. This approach reveals how fits

between technology and market innovations can help a

firm achieve superior performance when organizational

ambidexterity across domains helps balance the posi-

tive and negative outcomes of differentiation and low

cost strategies.

Market leveraging strategy. From an organizational

ambidexterity view, explorative technology innovation

and exploitative market innovation are complements.

First, the pursuit of completely new technologies or

Figure 2. Conceptual Model


827

products can create customer value, yet such innova-

tion usually incurs high costs and risks (He and Wong,

2004). To capture the benefits of this innovation and

reduce the potential for negative effects, the firm can

implement exploitative market innovation to serve

mainly existing markets and affirm existing relation-

ships with customers. Familiarity with customers and

distributors enables the firm to understand relevant

demands, trends, and technology opportunities, as well

as gain feedback about new technologies and products

(Fang et al., 2011). Thus, market exploitation should

mitigate the risks of new technology development

while also reducing market research and channel build-

ing expenses.

Second, technology exploration may provide a

means to leverage the benefits and overcome the dis-

advantages of market exploitation. Firms focusing on

new technologies can evaluate and respond to the

opportunities that stem from exploiting the current

market better, because they can develop diverse tech-

nology portfolios (Sorescu, Chandy, and Prabhu,

2003). The customer value created by new technolo-

gies also may lower customers’ price sensitivity, which

could enhance the firm’s profit margins in its current

market. Rather than suffering from inertia due to an

excessive focus on the current market (Zhou, 2006),

the ongoing technology exploration can help the firm

offset its resistance to change and motivate demands

among current customers for the radical new technolo-

gy (e.g., Apple’s iPhone). In turn, this strategy should

create growth opportunities in the existing market.

Technology leveraging strategy. Similarly, exploit-

ative technology innovation and explorative market

innovation should reinforce each other. Improvements

to current technologies are likely to lead to better qual-

ity, higher operational efficiency, and lower costs.

However, a heavy reliance on current technologies

may trap firms into “lock-in through learning” (Arthur,

1989) and result in dysfunctional rigidity that crowds

out new competencies (Leonard-Barton, 1992). To

avoid technology rigidity, the firm can explore new

markets by applying and adapting its current technolo-

gies to match the demands of diverse segments. This

approach expands the benefits of technology exploita-

tion (e.g., low cost, efficiency) across different markets

(Day and Moorman, 2010; Fang et al., 2011). Further-

more, by focusing on unsatisfied and emerging cus-

tomers, firms may achieve disruptive innovations

through redefining current technologies (Markides,

2006), and thus find a way out of “lock-in” risks.

Market exploration can be complemented by technolo-

gy exploitation because focusing on current technolo-

gies allows firms to acquire intensive knowledge and

reduce the uncertainties and cost of product innovation

(Prabhu, Chandy, and Ellis, 2005). These advantages

enable firms to develop suitable products to meet the

demands of new customers and enhance the possibility

of success in new markets.

H1: The interactions of (a) explorative technologyinnovation and exploitative market innovation and(b) exploitative technology innovation and explor-ative market innovation have positive effects onfirm performance.

Pure strategies. This study posits that pure explora-

tion and pure exploitation across domains are not opti-

mal arrangements. By offering advantages such as

innovativeness and novelty, pure exploration may

establish strongly differentiated identities (Day and

Moorman, 2010). However, firms that explore simulta-

neously across different domains are likely to face

undesirable uncertainties and risks (Danneels, 2002;

Lavie and Rosenkopf, 2006), due to their unfamiliarity

with the new market and the technology. In addition,

this strategy requires substantial investments many

firms cannot afford, and its rewards accrue only far in

the future (Day and Moorman, 2010). These negative

outcomes even may be amplified in emerging markets

with weak infrastructures (Jia, 2014; Marquis and

Qian, 2014). For example, private firms in China, a

market that remains dominated by the government

(Marquis and Qian, 2014), usually suffer from a chron-

ic shortage of strategic resources (Sheth, 2011). They

lack sufficient financial or human capital to search for

both new technologies and new markets. Their rela-

tively weak R&D and marketing capabilities usually

increase the risk of failure in totally new product–mar-

ket domains too. The extended timeframe and great

uncertainties of pure exploration also tend to be incon-

sistent or even conflict with the objectives of govern-

ment officials or authorities, who emphasize short-term

yields to ensure more tax income, faster growth, and

more rent-seeking opportunities (Jia, 2014). Firms pur-

suing totally new innovations may find it hard to

acquire resources or political legitimacy from local

authorities.

On the other hand, pure exploitation strategy can

promote operational efficiency and reduce uncertainties

(Day and Moorman, 2010) by leveraging experiences


F. ZHANG ET AL.

accumulated in an existing market and current technol-

ogies. However, the strategy is not beneficial in the

long term (Gupta et al., 2006). Exploiting existing stra-

tegic assets cannot create a sustainable competitive

advantage, because it traps firms into saturated “red

ocean” markets (Day and Moorman, 2010) that feature

abundant and homogenous rivals (Matusik and Hill,

1998). In addition, too much focus on existing technol-

ogies leads to firms’ aversion to change (Zhou, 2006)

and inertia (Aspara et al, 2011), as well as hinders

their ability to discover technology and market oppor-

tunities (Lavie and Rosenkopf, 2006). In emerging

markets that are undergoing transitions to market econ-

omies, rapid growth has stimulated fierce competitions

(Grosse and Ling, 2015) and increasingly diversified

consumer demands (Davies and Walters, 2004). The

efficiency achieved through the exploitation of current

technologies and markets thus becomes less critical, as

demonstrated in China’s household appliance market

for example. As Jansen et al. (2006) argue, exploita-

tion is not beneficial in dynamic or turbulent markets,

and it causes firms to fall behind the market. Finally,

the underdeveloped legal system of emerging markets

allows unregistered firms to persist and rely on their

cost and price advantages to survive (Jia, 2014; Mar-

quis and Qian, 2014). This gray market further aggra-

vates price competitions and leaves less space for

exploitation benefits.

H2: The interactions between (a) explorative tech-nology innovation and explorative market innova-tion and (b) exploitative technology innovationand exploitative market innovation have negativeeffects on firm performance.

Mediating Effects of Differentiation and Low CostAdvantages

In line with Day and Wensley’s (1988) source–posi-

tional advantages–performance framework, this study

argues that the performance effects of the two leverag-

ing configurations may be mediated by two positional

advantages, namely, differentiation and cost efficiency.

That is, a particular source (e.g., leveraging strategy)

can establish positional advantages (e.g., differentiation

and cost leadership positioning), which then enhance

firm performance (Day, 1994; Day and Nedungadi,

1994; Day and Wensley, 1988). Differentiation and

cost leadership offer two fundamental advantages that

may determine the success of a product innovation

(Kim and Atuahene-Gima, 2010; O’Cass et al., 2014).

These two advantages represent basic value superiori-

ties that customers perceive in evaluating competing

products (Kim and Atuahene-Gima, 2010). A differen-

tiation advantage results from unique or innovative

characteristics, such as superior product performance,

extended features or services, and strong brand aware-

ness (O’Cass et al., 2014; Zou et al., 2003). A low

cost advantage instead stems from cost efficiency,

such that the price for providing equivalent customer

value is lower than that charged by competitors

(Acquaah, 2007). Firms that perform well on differen-

tiation or cost efficiency create value for customers,

increase customer satisfaction and loyalty, and likely

achieve superior performance. Prior studies also estab-

lish links from different innovation activities to these

distinct advantages. For example, exploration tends to

enhance differentiation advantages, while exploitation

contributes to cost efficiency (Kim and Atuahene-

Gima, 2010; O’Cass et al., 2014).

The focus of market leveraging strategy on technol-

ogy exploration can ensure that the firm keeps up to

date with advanced technologies, creates new customer

value, and can differentiate itself from competitors

(Raisch and Birkinshaw, 2008). The focus on existing

segments also makes the assessment of the market

(e.g., judging the market potential of the new technol-

ogy) relatively accurate and efficient (Danneels, 2002),

and controls costs related to market development (e.g.,

brand building, distribution channels, sales promotions;

Day and Moorman, 2010). With this strategy, the firm

can balance the advantages of differentiation, by

developing new technologies, and low costs, by saving

market expenses.

Technology leveraging strategy focuses on refining

current technologies and requires relatively lower

R&D expenditures (O’Cass et al., 2014). It also seeks

to improve the efficiency of development and produc-

tion processes (Jansen et al., 2006), deepen more effi-

cient uses of organizational resources, and reduce

development time and cost (Morgan and Berthon,

2008). Therefore, this strategy can produce products at

lower costs (Smith and Tushman, 2005). With new

market exploration, firms also can find “blue ocean”

markets (Day and Moorman, 2010), which provide

new and disruptive business opportunities (Hang,

Chen, and Yu, 2011). Firms still attain innovativeness

and differentiation by applying their current technolo-

gies in new segments (Markides, 2006). Thus, this

strategy leads to differentiation, by positioning in a


829

new market, and low cost, by saving technology

expenses.

H3: Both (a) differentiation and (b) low costadvantages mediate the positive relationshipbetween market leveraging strategy and firmperformance.

H4: Both (a) differentiation and (b) low costadvantages mediate the positive relationshipbetween technology leveraging strategy and firmperformance.

Research Method

Research Setting and Sample

The data came from a survey of manufacturing and

service firms in China. Because of the massive and

rapid growth opportunities in China (Sheng et al.,

2011), competition among firms is fierce (Grosse and

Ling, 2015), as firms seek to serve increasingly diver-

sified customer demands by means of innovations

(Atuahene-Gima, 2005; Davies and Walters, 2004;

Zhou and Li, 2012). Innovations thus are being intro-

duced into China at an unprecedented pace (Zhou and

Wu, 2010), even though many Chinese firms face

strict resource constraints (Li and Zhang, 2007). To

survive the competition, firms must exploit their exist-

ing knowledge and also create new knowledge. Orga-

nizational ambidexterity may be specifically important

in China’s dynamic environment (Zhou and Wu,

2010). Therefore, China represents a suitable and inter-

esting study context.

A random sample of 600 firms located in the Bohai

Economic Development Delta of China was selected.

The Bohai Delta, which includes Beijing, Tianjin, and

Shandong provinces, is designated as a strategic devel-

opment area by China’s central government, exhibiting

strong economic performance and attracting many

firms to locate there. According to official statistics,

Shandong’s gross domestic product (GDP) is among

the top three in the nation, and Tianjin achieved the

most rapid GDP development in 2014, with 12.5%

annual growth compared with 2013. Well-known com-

panies that locate their headquarters there enjoy rela-

tively developed infrastructure and favorable policies,

including Haier and Hisense in Shandong province,

Lenevo in Beijing, and Ting Hsin in Tianjin. Further-

more, in response to the financial support and deregu-

lation policies by the government, numerous new

ventures start up in this area and technology enter-

prises constitute more than 20% of the total number of

firms. This study limited the investigation to these cit-

ies, in line with prior studies that acknowledge the

challenges and high costs of data collection in China

(e.g., Fang, 2011; Kim and Atuahene-Gima, 2010; Li

and Atuahene-Gima, 2001; Sheng et al., 2011; Zhou

and Li, 2012).

Two criteria were adopted to screen firms. First,

each firm must have engaged in at least one type of

innovation activities related to a new or improved

product, process, or technology in the previous 3

years. Second, the firm must have achieved a mini-

mum scale. Self-employed or micro-firms with less

than five full-time employees were excluded. The final

sample includes both manufacturing and service firms,

which helps avoid industry-specific influences and

increases generalizability across industrial sectors. Pri-

or studies conducted similarly relevant surveys related

to exploration and exploitation in both manufacturing

and service firms (e.g., He and Wong, 2004; Voss, Sir-

deshmukh, and Voss, 2008).

Questionnaire Design and Data Collection

Based on a thorough review of the literature, this study

developed measurement items for each construct in

English, translated the items into Chinese, and translat-

ed them back into English. Changes were made to

address inconsistencies. To ensure the relevance of the

questionnaire to the Chinese context (Li and

Atuahene-Gima, 2001; Zhou and Li, 2012), this study

conducted a focus group with 10 senior managers and

three strategic management professors who were

knowledgeable about product and market innovation

activities and were asked to provide insights into the

measures of the four configurations. These experts

assessed all the survey items and offered feedback,

leading to some minor adjustments in the survey. A

pilot study was also conducted with graduate business

students from a university in China to further refine

the questionnaire.

Because Chinese managers are very sensitive about

industrial espionage and data protection, the difficulty

of collecting survey data in China requires specific

methods (Fang and Zou, 2009; Li and Atuahene-Gima,

2001), including high personal involvement by

researchers (e.g., Kim and Atuahene-Gima, 2010; Li

and Atuahene-Gima, 2001; Li, Poppo, and Zhou,

2008; Zhou and Li, 2012). Senior or middle managers


F. ZHANG ET AL.

(e.g., chief executive officer, vice president, general or

middle marketing manager, R&D manager) who were

familiar with the firm’s technology and market innova-

tions were selected as key informants. Specifically,

appointments were scheduled with all potential respond-

ents to explain the academic purpose of the survey and

confirm if the firm had engaged in any innovation activ-

ities in the past 3 years. The informants were assured of

the confidentiality of their responses to encourage their

participation. Firms that did not meet these criteria or

were unwilling to participate were eliminated. Question-

naires were then distributed to key informants who

agreed to participate. After a month, those who had not

responded were reminded with a telephone call.

After removing responses with missing data for the

key constructs, 292 valid responses were retained in

the sample. The valid response rate of 48.7% is similar

to that in other studies in emerging markets (e.g.,

36.8%: Li and Atuahene-Gima, 2001; 48.2%: Sheng

et al., 2011; 38.4%: Zhou and Wu, 2010). To check

for nonresponse bias, early and late respondents were

compared on all observed variables (Armstrong and

Overton, 1977). T-test results showed no difference

between groups (p> .05), indicating that nonresponse

bias was not a concern. Table 2 shows the profiles of

the respondents and their firms.

Measures

The measures are listed in the Appendix. Firm perfor-mance was considered as a multidimensional construct

and therefore measured in terms of sales, market share,

profitability, return on assets, and customer satisfaction

(see Sheng et al., 2011). Using self-reports, respond-

ents were asked to indicate their firms’ performance in

the previous 3 years, as compared with the perfor-

mance of their major competitors.

Explorative technology innovation, exploitative

technology innovation, explorative market innovation,

and exploitative market innovation were measured

using scales in previous studies (e.g., He and Wong,

2004; Jansen et al., 2006; McDermott and Prajogo,

2012). Respondents were asked to evaluate the impor-

tance of the relative objectives for undertaking multi-

ple projects in technology or market domains in the

previous 3 years. To ensure the validity of these four

measures, this study conducted exploratory factor anal-

ysis during the pilot study and confirmatory factor

analysis in the final stage, revealing a satisfactory fit

(v2(d.f.) 5 261.96(113), root mean square error of

approximation [RMSEA] 5 .067). Next, the measures

of differentiation and low cost advantages were from

Acquaah (2007); Hughes, Martin, Morgan, and Robson

(2010); Vorhies, Morgan, and Autry (2009); and Zou

et al. (2003). Respondents evaluated their firms’ strate-

gic positions or advantages in the previous 3 years,

compared with their major rivals.

Finally, several variables that might have effects on

the results were controlled. Firm size signals the amount

of resources available to create new products, develop

new markets, and acquire competitive advantages,

which may affect performance (Kim and Atuahene-

Gima, 2010). Compared with large firms, small and

Table 2. Profile of Responding Firms and Participants

Characteristics Frequency Percentage (%)

Position of respondents General manager 132 45.2

Middle manager 148 50.7

Junior managers or professionals

(marketing or R&D)

12 4.1

Firm age Less than 3 years 28 9.6

3–5 years 43 14.7

6–10 years 56 19.2

More than 10 years 164 56.2

No answer 1 .3

Firm size Below 100 59 20.2

100–300 58 19.9

300–800 43 14.7

More than 800 132 45.2

Industry type Manufacturing (e.g., household appliance,

electronic, and chemical industries)

144 49.3

Service (e.g., software, banking,

and communications)

131 44.9

No answer 17 5.8


831

medium firms may lack the resources needed to support

explorative or radical innovations. Firm size, measured

as the number of full-time employees, was controlled.

New firms may suffer a liability of newness and lack

experience, resulting in poorer performance compared

with older firms that have abundant experience. Firmage was also controlled. The manufacturing and service

industries also constitute distinctive contexts (Voss and

Voss, 2013). For example, compared with manufactur-

ing, the service sector tends to be more active and crea-

tive in exploring the market to identify customer

preferences (Kim and Atuahene-Gima, 2010). Voss and

Voss (2013) also point to potential differences and

influences on organizational ambidexterity. Therefore,

industry type was controlled.

Analyses and Results

Common Method Bias

Both procedural and statistical remedies were used to

address common method bias. First, this study used

multiple-item measurements, well-designed scales,

reverse-coded items, systematic back-translation and

refinement of the questionnaire, and guarantees of ano-

nymity when creating the survey instrument (Lindell

and Whitney, 2001; Podsakoff, MacKenzie, Lee, and

Podsakoff, 2003). Second, Harman’s one-factor test was

applied to check for the presence of this bias. In an

exploratory factor analysis, seven factors were

identified, including one dependent variable, four inde-

pendent variables, and two moderators. The first factor

only explained 13% of the total variance. Third, a mark-

er variable (MV) technique was applied (Lindell and

Whitney, 2001). The MV of organizational complexity

was not only theoretically but also empirically unrelated

to both the independent and dependent variables in the

study. The smallest correlation between the MV and

other variables (r 5 .003) was used to adjust the correla-

tions matrix and statistical significances (see Table 3).

Fourth, following Lindell and Whitney (2001), a more

stringent sensitivity analysis was conducted, in which both

the second smallest correlation between the MV and other

variables (r 5 .011) and an upper limit of a 99% confi-

dence interval of the smallest correlation (r 5 .003) were

used to make the adjustment. As Table 4 reveals, after

these adjustments, the correlations remained statistically

significant. Fifth, the focus on the interaction terms further

reduced concerns of common method bias, because it was

almost impossible for respondents to infer the theorized

relationships in the study. Thus, common method bias was

not likely to be a concern.

Reliability and Validity

Construct validity was examined using confirmatory

factor analysis. All items loaded significantly on their

expected constructs (p< .01). The fit indices showed

that the overall model provided acceptable fit (v2

Table 3. Descriptive Statistics and Correlations

Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1 4.829 1.378 .800 .641** .462** .492** .531** .289** .346**

2 5.295 1.273 .643** .825 .575** .645** .464** .281** .350**

3 5.182 1.179 .464** .576** .755 .683** .379** .326** .331**

4 5.476 1.122 .494** .646** .684** .812 .372** .261** .330**

5 4.756 1.163 .532** .466** .381** .374** .781 .616** .619**

6 4.447 1.177 .291** .283** .328** .263** .617** .825 .564**

7 4.856 1.158 .348** .352** .333** .332** .620** .565** .775

8 .199 .400 2.003 2.018 2.053 2.129* .019 .035 2.020

9 .147 .355 2.014 2.127* 2.021 2.067 2.007 .019 .081 2.207**

10 .452 .499 .005 .072 .030 .124* .030 2.025 .080 2.452** 2.377**

11 .147 .355 .021 .040 .092 .052 2.022 2.049 2.019 .108 2.064 2.222**

12 .192 .394 2.070 2.070 2.138* 2.098 2.019 .037 2.071 .150* .092 2.180** 2.202**

13 .562 .497 .037 .013 .006 .029 .051 .019 .168* 2.166** 2.022 .428** 2.470** 2.551**

14 .524 .500 .110 .060 2.063 2.092 .044 2.072 .029 2.023 .041 .161** 2.061 2.078 .196**

15 4.582 1.665 .056 2.018 .003 2.015 2.033 .011 .073 2.030 2.082 .319** 2.093 2.144** .243** 2.005

Notes: N 5 292. Zero-order correlations are below the diagonal; adjusted correlations for potential common method variance (Lindell and Whitney,

2001) are above diagonal. Bold numbers on the diagonal show the square root of the average variance extracted. 1. Explorative Technology Innova-

tion; 2. Exploitative Technology Innovation; 3. Explorative Market Innovation; 4. Exploitative Market Innovation; 5. Differentiation Advantages; 6.

Low Cost Advantages; 7. Firm Performance; 8. Firm Scale_dummy1; 9. Firm Scale_dummy2; 10. Firm Scale_dummy3; 11. Firm Age_dummy1; 12.

Firm Age_dummy2; 13. Firm Age_dummy3; 14. Industry Type_dummy; 15. Organizational Complexity (MV).

* p< .05. **p< .01.


F. ZHANG ET AL.

(d.f.) 5 1310.47(413), RMSEA 5 .086, square root

mean residual 5 .062). Furthermore, Cronbach’s alphas

ranged from .84 to .90, above the accepted benchmark

of .70 (Nunnally, 1978). The average extracted varian-

ces (AVE) of all constructs (from .57 to .68) were

higher than the recommended .5 level (Hair, Anderson,

Tatham, and Black, 1998). These measures demon-

strated adequate convergent validity and reliability.

The square root of the AVE of each construct was

greater than the correlation of the construct with all

other constructs in the model (Table 3), in support of

discriminant validity (Fornell and Larcker, 1981).

Hypotheses Testing

The satisfactory validation of the scales suggested that

hierarchical regression analyses be conducted to test

the hypotheses. The means, standard deviations, and

correlations of the variables are shown in Table 3. To

mitigate the potential threat of multicollinearity, this

study mean-centered both independent and moderating

variables, then created interaction terms by multiplying

the mean-centered variables (Aiken and West, 1991).

The variance inflation factors were below 10.0, so

multicollinearity was not a concern. To assess the

explanatory power of each set of variables, the varia-

bles in the model were included block by block.

As shown in Table 5, the R-square difference (.047)

between Model 3 (with interaction effects) and Model

2 (without interaction effects) was significant (p< .01).

Furthermore, the interaction terms in Model 3

indicated that the explorative technology–exploitative

market innovation condition (i.e., market leveraging

strategy) was positively associated with firm perfor-

mance (b 5 .376, p< .01), in support of H1a. The inter-

action of exploitative technology with explorative

market innovation (technology leveraging strategy) was

found marginally significant (b 5 .203, p< .1), in sup-

port of H1b. However, the interaction of explorative

technology and market innovations (pure exploration

strategy) had no significant effect (b 5 2.050, p> .1),

so H2a was not confirmed. The interaction of exploit-

ative technology and market innovations (pure exploita-

tion strategy) was negatively associated with firm

performance (b 5 2.415, p< .01), in support of H2b.

Figure 3 contains the results of simple slope analyses,

in which this study decomposed the significant interac-

tions and compared the impact of technology explora-

tion or exploitation on firm performance at low and high

levels of market exploration or exploitation (Aiken and

West, 1991). The low levels were one standard deviation

below the mean score, and the high levels were one stan-

dard deviation above it. Panel A indicates that technolo-

gy exploration had a positive effect on firm performance

at the high level of market exploitation, but a negative

effect at the low level. According to Panel B, technology

exploitation had a stronger positive effect on firm perfor-

mance at the high rather than the low level of market

exploration. Panel C illustrates the negative exploitation

interaction, suggesting technology exploitation had a

negative effect at the high level of market exploitation,

but a positive effect at the low level.

Table 4. Sensitivity Analysis about MV-Marker Test

Constructs 1. 2. 3. 4. 5. 6. 7. 8.

1. Explorative technology

innovation

.639**

(.578**)

.458**

(.367**)

.488**

(.403**)

.527**

(.447**)

.283**

(.163**)

.341**

(.230**)

2. Exploitative technology

innovation

.643** .571**

(.499**)

.642**

(.582**)

.460**

(.370**)

.275**

(.153**)

.345**

(.235**)

3. Explorative market

innovation

.464** .576** .680**

(.627**)

.374**

(.269**)

.321**

(.207**)

.326**

(.213**)

4. Exploitative market

innovation

.494** .646** .684** .367**

(.261**)

.255**

(.130*)

.325**

(.211**)

5. Differentiation advantages .532** .466** .381** .374** .613**

(.548**)

.616**

(.551**)

6. Low cost advantages ..291** .283** .328** .263** .617** .560**

(.486**)

7. Firm performance .348** .352** .333** .332** .620** .565**

8. Organizational

complexity (MV)

.056 2.018 .003 2.015 2.033 .011 .073

Notes: N 5 292. Zero-order correlations are below the diagonal; adjusted correlations for potential common method variance (Lindell and Whitney,

2001) are above diagonal; the numbers above parentheses represent the adjusted correlations using second smallest correlation between the MV and other

variables (.011), and numbers in parentheses represent the adjusted using the upper limit of 99% confidence interval of the smallest correlation (.153).

* p< .05. **p< .01.


833

As predicted in H3 and H4, both market leveraging

and technology leveraging strategies are mediated by

differentiation and low cost advantages. That is, this

study aims to reveal why and how ambidexterity

across domains result in superior performance. These

hypotheses were examined with a three-step mediation

test (Baron and Kenny, 1986; Kim and Atuahene-

Gima, 2010). The procedures and results are shown in

Table 6. For example, for the test of H3a, the direct

effect of the independent variable (market leveraging

strategy) on the dependent variable (firm performance)

appeared in Model 1 of Table 6 (b 5 .131, p< .05).

Figure 3. Simple Slope Analyses

Table 5. Results for Effects of Configuration Strategies on Firm Performance

Constructs

Performancea

Model 1 Model 2 Model 3 Model 4

Explorative technology innovation .140 .053 .053

Exploitative technology innovation .184* .217* .243**

Explorative market innovation .132 .166* .194*

Exploitative market innovation .070 .086 .076

Explorative technology 3 exploitative market .376** .375**

Explorative technology 3 explorative market 2.050 2.042

Exploitative technology 3 exploitative market 2.415** 2.405**

Exploitative technology 3 explorative market .203b .200b

Industry Type_dummy 2.021 2.036 2.025 2.024

Firm Scale_dummy1 .062 .059 .081 .074

Firm Scale_dummy2 .128 .150* .189** .159*

Firm Scale_dummy3 .067 .041 .082 .052

Firm Age_dummy1 .129 .151 .166* .137

Firm Age_dummy2 .085 .180 .161 .138

Firm Age_dummy3 .257* .336** .332** .309**

R2 .045 .233 .279 .302

Adjusted R2 .019 .201 .238 .261

F 1.778 7.253** 6.693** 7.458**

�R2 .188** .047** .048**

aMeasured without customer satisfaction in Model 1, 2, 3, with all items in Model 4.bMarginally significant at the level of .1.

*p< .05. **p< .01.


F. ZHANG ET AL.

Ta

ble

6.

Res

ult

sfo

rM

ed

iati

on

so

fD

iffe

ren

tia

tio

na

nd

Lo

wC

ost

Ad

va

nta

ges

H3

aH

3b

H4

aH

4b

Dep

enden

tvar

iable

s

(sta

ndar

diz

edco

effi

cien

ts)

Model

1

per

form

ance

Model

2

dif

fere

nti

atio

n

Model

3

per

form

ance

Model

4

low

cost

Model

5

per

form

ance

Model

6

per

form

ance

Model

7

dif

fere

nti

atio

n

Model

8

per

form

ance

Model

9

low

cost

Model

10

per

form

ance

Ind

epen

den

t(i

nte

ract

ions)

Mar

ket

lever

agin

gst

rate

gy

.131*

.132*

.057

.121*

.073

Tec

hnolo

gy

lever

agin

gst

rate

gy

.106

.110*

.043

.125*

.046

Med

iato

rs

Dif

fere

nti

atio

nad

van

tages

.563**

.566**

Low

cost

advan

tages

.478**

.482**

Contr

ols

Explo

rati

ve

tech

nolo

gy

innovat

ion

.115

.343**

2.0

78

.118

.058

.136

.364**

2.0

70

.137

.070

Explo

itat

ive

tech

nolo

gy

innovat

ion

.211*

.191*

.103

.113

.157*

.183*

.163*

.091

.087

.141

Explo

rati

ve

mar

ket

innovat

ion

.141

.119

.074

.251**

.021

.155

.134

.079

.270**

.025

Explo

itat

ive

mar

ket

innovat

ion

.095

.051

.067

.011

.090

.093

.049

.065

.014

.086

Ind

ust

ryT

ype_

dum

my

2.0

34

2.0

12

2.0

27

2.0

86

.007

2.0

32

2.0

10

2.0

26

2.0

83

.008

Fir

mS

cale

_dum

my1

.069

.061

.035

.066

.038

.078

.071

.038

.079

.040

Fir

mS

cale

_dum

my2

.168*

.064

.132*

.053

.143*

.171*

.068

.132*

.061

.142*

Fir

mS

cale

_dum

my3

.069

.062

.034

.011

.064

.062

.055

.031

.009

.057

Fir

mA

ge_

dum

my1

.145

.015

.137*

2.0

16

.153*

.141

.011

.135*

2.0

22

.152*

Fir

mA

ge_

dum

my2

.164

.078

.120

.115

.109

.163

.076

.120

.110

.110

Fir

mA

ge_

dum

my3

.317**

.081

.271**

.092

.272**

.321**

.084

.273**

.092

.276**

R2

.248

.343

.455

.175

.436

.242

.338

.454

.175

.434

Adj

uste

dR

2.2

13

.313

.428

.137

.408

.207

.308

.427

.137

.405

F7.1

81**

11.4

00**

16.7

91**

4.6

19**

15.5

45**

6.9

71**

11.1

54**

16.7

12**

4.6

30**

15.3

66**

Not

es:

*p<

.05.

**p<

.01.


835

Then the direct effect of the independent variable on

the mediator (differentiation advantage) was examined,

as in Model 2 (b 5 .132, p< .05). Finally, the direct

effect of the mediator (differentiation advantage) on

the dependent variable (firm performance) was noted

while controlling for the independent variable (market

leveraging strategy) in Model 3. If the effect of the

independent variable on the dependent variable is not

significant after adding the mediator to the model, full

mediation is indicated. Compared with Model 1, the

positive effect of market leveraging strategy became

weak and even insignificant in Model 3 (b 5 .057,

p> .1), whereas the differentiation advantage had a

significant impact on performance (b 5 .563, p< .01).

Therefore, differentiation advantage mediated the rela-

tionship between market leveraging strategy and firm

performance, in support of H3a. Similarly, a full medi-

ation effect was found for low cost advantage on the

relationship between market leveraging strategy and

firm performance (H3b). Similarly, H4a and H4b were

supported (Table 6).

To further validate the statistical significance of

these mediation effects, Sobel (1988) test was con-

ducted and the indirect effects through the mediators

for each mediation effect were calculated. With regard

to H3a, the indirect effect of market leveraging strate-

gy through differentiation explained 56.7% of the total

effect on firm performance, and the indirect effect was

significant at the 5% level (z 5 2.357). For H3b, the

indirect effect of market leveraging strategy through

low cost explained 44% of its total effect, and was

also significant (z 5 1.931). Regarding H4a and H4b,

the indirect effects of technology leveraging strategy

through differentiation and low cost advantages

explained 59.2 and 57.1%, respectively, and both were

significant (z 5 1.934 and 1.957). Therefore, the medi-

ating effects were strongly supported. Moreover, both

differentiation and low cost advantages fully mediated

the effects of market leveraging and technology

leveraging strategies. This implies that the positive

effects of the two mixed strategies on firm perfor-

mance (H1 and H2) can be achieved only by first

attaining differentiation advantage from explorative

innovations and low cost advantage from exploitative

innovations (O’Cass et al., 2014).

A robustness test was conducted in which firm perfor-

mance was measured using different items (Model 4 in

Table 5). The results remained consistent in terms of the

effects of the four configurations on firm performance

(i.e., effect size, positive or negative sign, and significance

levels). A subgroup analysis based on industry type

(manufacturing versus service firms) also produced con-

sistent results. These additional analyses confirmed the

robustness of the results and the veracity of the findings.

Discussion

This study investigates configurations of innovations

across domains and reveals how different configura-

tions influence firm performance. Different from previ-

ous research that focuses primarily on technology-

related innovation (Aspara et al., 2011; Sidhu et al.,

2007) or organizational ambidexterity in one specific

domain (He and Wong, 2004; Vorhies et al., 2011;

Zhang et al., 2012), this article instead distinguishes

exploration and exploitation in technology-related and

market-related innovations and reveals how to config-

ure these two categories to achieve superior perfor-

mance. In particular, four configurations have different

impacts on firm performance. Explorative technology

innovation combined with exploitative market innova-

tion had a beneficial interactive effect, so did the com-

bination of exploitative technology innovation with

explorative market innovation. In contrast, pure explo-

ration strategy had no significant effect on firm perfor-

mance while pure exploitation strategy exerted a

negative effect. These results resonate with the organi-

zational ambidexterity research, especially the notion

of domain separation (Lavie and Rosenkopf, 2006;

Lavie et al., 2011) and the demand for simultaneous

exploration and exploitation to ensure long-term suc-

cess (He and Wong, 2004; O’Reilly and Tushman,

2008; Voss and Voss, 2013). The results also affirmed

the negative influence of a singular focus (Levinthal

and March, 1993; Volberda and Lewin, 2003), despite

Voss and Voss’s (2013) claim of positive effects of

pure exploitation or exploration across domains. This

article attributes these contradictory findings to the dis-

tinct study context. In emerging markets like China,

marked by resource deficiency (Sheth, 2011), expropria-

tion risks (Li and Atuahene-Gima, 2001), and great

dynamism (Zhou and Poppo, 2010), the negative effects

of pure exploration or exploitation may be amplified.

This study also reveals how configurations affected

firm performance by examining the mediating effects

of differentiation and low cost advantages, through

which the promise of organizational ambidexterity can

be achieved. The validation of these indirect effects

supported the source–position advantage–performance

chain proposed by Day and Wensley (1988). In line

with prior studies (e.g., Kim and Atuahene-Gima,


F. ZHANG ET AL.

2010; O’Cass et al., 2014), this study confirms that

positional advantages are key for explaining how an

innovation strategy can lead to superior performance.

Theoretical Implications

This study contributes to the organizational ambidex-

terity literature by examining the balance of explora-

tion and exploitation across two domains

simultaneously, namely, technology-related and

market-related innovations. In so doing, this article

responds to the call for ambidexterity research across

business domains (Lavie and Rosenkopf, 2006; Lavie

et al., 2011). Lavie and colleagues investigate explora-

tion and exploitation across the broader scope of a

firm’s functions, structures, and attributes in interorga-

nizational alliances. This study instead applies domain

separation to two intra-organizational activities. With

this approach, the study highlights the need to coordi-

nate strategic objectives or behaviors across closely

related domains and balance exploitation and explora-

tion simultaneously. The conceptual framework is also

established for coping with innovation dilemmas,

namely, by configuring technology- and market-related

innovations according to an organizational ambidexter-

ity perspective (He and Wong, 2004; March, 1991;

Tushman and O’Reilly, 1996), to relieve the tensions

of technology- versus market-related innovations and

exploitation versus exploration. The findings confirmed

the importance of suitable configurations, revealing the

interaction effects of different configuration strategies,

which can help resolve controversies related to the

mixed effects of organizational ambidexterity that

appear in previous research and practice (Lavie and

Rosenkopf, 2006; Lavie et al., 2011).

Furthermore, using the source–position advantage–

performance framework, this study demonstrates the

full mediating effects of differentiation and low cost

advantages, establishing that the positive effects of

market and technology leveraging strategies on firm

performance require differentiation and low cost

advantages to be effective. Organizational ambidexteri-

ty across domains also may provide an important

source of competitive advantages and represent a

firm’s efforts to translate its technology- and market-

based resources into both differentiation and low cost

advantages. This article thus emphasizes the impor-

tance of organizational ambidexterity and illustrates

fundamentally how and why ambidexterity across

domains is able to achieve superior performance. This

insight deepens and extends the understanding of the

performance effects of organizational ambidexterity,

and it provides important complements to prior studies

(e.g., Danneels, 2002; Voss and Voss, 2013).

By deriving these insights from a survey conducted

in China, this study contributes further to the relevant

literature. As the world’s largest emerging market,

China shares many common features with other

emerging markets (Sheng et al., 2011), so the study

suggests some important implications. In particular,

this study finds an amplified negative effect of pure

exploration or exploitation configuration in an under-

developed dynamic institutional environment. The

inconsistency of this result with the U.S.-based find-

ings of Voss and Voss (2013) underlines the impor-

tance of adapting relevant theories to emerging

markets. It also suggests an interesting direction for

research, which could test these findings in various

emerging markets.

Finally, in line with the theoretical assertion that

the proper configuration of organizational elements

and activities (e.g., functions, structures, attributes) is

critical for achieving firm performance (Siggelkow,

2002), this study provides empirical evidence of the

impacts of such configurations. Unlike previous studies

that focus on technology-related innovations alone,

this study reveals the inherent relationship between

two different but complementary innovation activities,

which suggests different approaches to manage this

critical trade-off. This study represents the first empiri-

cal evidence related to the configurations of different

innovation activities within the firm, as well as new

understanding of the mechanisms by which these con-

figurations impact firm performance, through a mediat-

ed path.

Practical Implications

This study offers guidelines for managers of both local

and foreign firms in emerging markets. As the Chinese

government has increased its openness, the largest

market in the world has attracted multinational firms.

New product development is strategically critical for

these multinationals, in their efforts to enhance local

consumers’ responsiveness. This study, conducted in

the Chinese market, thus has important implications

for managers running multinational businesses in Chi-

na and those planning to enter the market. First, the

findings suggest managers should undertake both

exploration and exploitation and avoid pure strategies.


837

They can achieve this balance across different func-

tional areas and thereby manage the trade-off between

exploitation and exploration more effectively. To

achieve innovation success and superior performance,

market leveraging and technology leveraging strategies

appear appropriate, because they can lead to differenti-

ated customer value at relatively low cost, producing

competitive advantages over competitors.

Second, the additional analysis based on subgroups

suggests that large and small firms may benefit from

different ambidextrous strategies. Large firms with suffi-

cient resources to support expensive R&D can pursue

market leveraging strategy, develop innovative products,

and maintain unique advantages in current markets. The

regression coefficient for the effects of the market

leveraging strategy on firm performance is .546 and sta-

tistically significant (p< .05). Technology leveraging

strategy instead may be more suitable for small firms

with limited strategic resources. The regression coeffi-

cient for the effects of the technology leveraging strate-

gy on firm performance is .438 and statistically

significant (p< .05). In other words, small firms might

exert more effort to find niche markets that have been

neglected by larger competitors, or they may implement

a blue ocean strategy to avoid fierce competition.

Third, in relation to the finding that differentiation and

low cost advantages represent mediating mechanisms

through which configurations of innovations lead to supe-

rior firm performance, this study recommends that firms

manage and configure their innovation processes to bal-

ance the positive benefits (i.e., differentiation) against the

negative effects (i.e., costs and risks) (Day and Moorman,

2010). Otherwise, they will suffer the dilemmas of insuf-

ficient innovation or unaffordable investment. An innova-

tion strategy will result in superior performance only if

the firm can effectively coordinate its differentiation and

low cost advantages. In this coordination effort, managers

also should ensure a technology–market link, by integrat-

ing and configuring different innovation activities to

achieve internal fit, rather than considering them separate-

ly. Superior performance can be achieved by making full

use of the benefits of organizational ambidexterity, name-

ly, by configuring innovation strategies properly along

exploitation and exploration and along technology-related

and market-related innovations.

Limitations and Research Directions

This preliminary effort to study organizational ambi-

dexterity in a complex context with underdeveloped

institutions and dynamic market environments also

suggests several limitations that may direct further

research. First, the negative effects of pure exploitation

strategy and insignificant effects of pure exploration

strategy were found (cf. Voss and Voss, 2013). The

potential benefits and consequences of such pure strat-

egies were not discussed in this study. Future research

can explore the possible benefits of these two configu-

rations and specify the nature of the effects (positive,

negative, insignificant) to reveal when, how, and why

such effects may exist or even be effective in specific

contexts.

Second, a combination of procedural and statistical

remedies were used to avoid common method bias,

but additional research should seek to collect more

objective data from multiple sources. For example, fur-

ther studies could survey multiple informants from the

same firm or collect objective performance data to

confirm the generalizability of the findings. Additional

cross-sectional studies may avoid the costs and time

demands of longitudinal studies (Li and Atuahene-

Gima, 2001), but some caution about the casual link-

ages in the study should be noted, due to the inherent

limitations of cross-sectional studies. Thus, a longitudi-

nal study would be helpful. Perceptual measures were

used in this study, and these perceptions may differ

from reality. Objective measures from archival sources

could overcome such possible biases and improve the

rigor of the results.

Third, many factors may influence firms’ innovation

activities and thus deserve more research attention,

including social networks, top management teams,

internal business processes, environmental dynamism,

and other contextual factors (e.g., R&D intensity,

resource dependency). China and other emerging econ-

omies still vary greatly in their economic development

and institutional environment, yet common features

exist across countries. Further research needs to con-

firm the validity of the results when applied to other

emerging markets, beyond the Chinese context.

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Appendix: Measurement Items and Validity Assessment

Items SFL

Explorative Technology Innovation (evaluating importance of the following objectives for

undertaking innovation projects in the last 3 years): adapted from Jansen et al. (2006),

He and Wong (2004), and McDermott and Prajogo (2012). CA 5 .9, AVE 5 .64

1. Introduce new generation of technology .76

2. Extend technology range .73

3. Pursue new potential technology .83

4. Adventure of developing new products or technology .86

5. Enter new technology fields .80

Exploitative Technology Innovation: adapted from Jansen et al. (2006), He and Wong (2004), and McDermott

and Prajogo (2012). CA 5 .89, AVE 5 .68

1. Improve existing product quality .85

2. Refine existing technology .89

3. Improve production process and engineering technology .88

4. Reduce production cost .66

Explorative Market Innovation: adapted from Jansen et al. (2006), He and Wong (2004), and McDermott


1. Open up new markets .71

2. Acquire customers with different profiles and behavior patterns .77

3. Establish relationships with diverse customers .84

4. Establish relationships with diverse channel members .69

Exploitative Market Innovation: adapted from Jansen et al. (2006), He and Wong (2004), and McDermott


1. Expand existing market .70

2. Develop deep knowledge about existing customers’ profiles and behavior patterns .85

3. Expand offerings for existing customers .87

4. Establish strong relationships with existing customers .81

Differentiation advantages (in comparisons with major competitors, evaluating firms’ relative

advantages in the last 3 years): adapted from Acquaah (2007), Zou et al. (2003), Vorhies et al. (2009),

and Hughes et al. (2010). CA 5 .89, AVE 5 .61

1. Products uniqueness .88

2. Markets newness .87

3. Brand awareness .71

4. Delivery speed and reliability .75

5. Technical support and after-sales service .69

Low Cost Advantages: adapted from Acquaah (2007), Zou et al. (2003), Vorhies et al. (2009), and

Hughes et al. (2010). CA 5 .89, AVE 5 .68

1. Raw material cost .87

2. Unit production cost .90

3. Channels building and maintaining cost .76

4. Sales cost .76

Performance (in comparisons with major competitors, evaluating firms’ performance in the last 3 years). CA 5 .88, AVE 5 .60

1. Sales .73

2. Market share .74

3. Profitability .88

4. Return on assets .87

5. Customer satisfactiona .63

Notes: Overall model fit: v2 (d.f.) 5 1310.47(413), root mean square error of approximation 5 .086, square root mean residual 5 .062, normed fit

index 5 .94, nonnormed fit index 5 .95, confirmatory fit index 5 .96. SFL 5 standardized factor loading, CA 5 Cronbach’s alpha, AVE 5 average vari-

ance extracted.aDropped from hypotheses testing because of the low loading.


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Configurations of Innovations across Domains: An ... · neels, 2002; Sidhu et al., 2007). However, most of the literature focuses on technology, leaving “rather little explicit