SOCIAL CAPITAL EMERGENCE AND THE CO-EVOLUTION OF ORGANIZATIONAL CAPABILITIES CHRISTOPHER FREDETTE A DISSERTATION SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN ADMINISTRATION YORK UNIVERSITY, TORONTO, ONTARIO AUGUST 2009
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SOCIAL CAPITAL EMERGENCE AND THE
CO-EVOLUTION OF ORGANIZATIONAL CAPABILITIES
CHRISTOPHER FREDETTE
A DISSERTATION SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
GRADUATE PROGRAM IN ADMINISTRATION
YORK UNIVERSITY,
TORONTO, ONTARIO
AUGUST 2009
iv
ABSTRACT
This dissertation explores the relationship between social capital and an
organizational capability during the earliest phases of emergence. Using an
experimental methodology based on a virtual crisis simulation, this research examines
the influence of social capital emergence on the evolution of capability performance in
real time. Results illustrate the cross-sectional, autoregressive, and cross-lagged change
in social capital and capability performance over three measurement intervals,
suggesting the presence of a co-evolving relationship between the two constructs. This
dissertation contributes valuable insight to the management literature by examining the
micro-foundations of organizational capability emergence; demonstrating that the
social, relational, and structural context of work is central, especially in its ability to
shape collaborative practice and contribute to the collective ability to meet
organizational needs. This study demonstrates how the process of social capital
emergence occurs, and explains how it relates to the triggering of capability evolution.
As a result, this dissertation has generated greater insight into how organizational
capabilities grow and evolve, and how social capital contributes to these processes. By
better understanding the role that social capital networks play in the emergence and
evolution of organizational capabilities, we add some measure of control and
predictability to capability evolution allowing organizations to take action to encourage,
stabilize, or discourage capability change via specific intervention mechanisms, and
v
provide an opportunity to maintain alignment between internal processes and
performance objectives.
vi
DEDICATION
Two roads diverged in a yellow wood, And sorry I could not travel both And be one traveler, long I stood
And looked down one as far as I could To where it bent in the undergrowth.
Then took the other, as just as fair,
And having perhaps the better claim, Because it was grassy and wanted wear;
Though as for that the passing there Had worn them really about the same.
And both that morning equally lay
In leaves no step had trodden black. Oh, I kept the first for another day!
Yet knowing how way leads on to way, I doubted if I should ever come back.
I shall be telling this with a sigh
Somewhere ages and ages hence: Two roads diverged in a wood, and I--
I took the one less traveled by, And that has made all the difference.
Robert Frost (1915), The Road Not Taken I dedicate this work and all of the effort it entailed to the people in my life that helped me find my path, held my hand along the journey, kept the rain off my shoulders, and gave me shelter when I needed it most. Each of you has touched me beyond words. I am not naïve enough to believe that this would have been possible without the love and support of my Nicole, whose constant companionship has given me strength through my darkest hours. For this I am forever grateful. My life has been shaped by our family, to them I owe a special debt for teaching me the value of work, the virtue of perseverance, and a love of learning. Along the way I have been fortunate to have been joined by wonderful travelling companions, but have also lost one or two. Grandpa, I miss you every day. I have watched as mentors became friends, and as friends became mentors. Christine Oliver, you are an inspiration to me and a model that I can only aspire to emulate in
vii
some small way. Ellen Auster, you have been an outstanding mentor and motivator, always pushing me to “go for it” even when I was unsure. Oana Branzei, you have shown me what commitment to the craft means, and how to achieve and over-achieve time and time again. While I may have moved more quickly had I traveled lighter, taking the trip without my classmates would have been unthinkable. You have all endured endless ribbing and prodding over the years and deserve at least this small note of thanks.
Figure 5-1: Structural Equation Model of Hypotheses with Comparative Cross-Sectional Relationships……………………………………………………………… 135 Figure 5-2: Latent Growth Curve Model (Curve of Factors Model)……………………….. 154
Figure 5-3: Average Growth Curves of Second Order Factors……………………………….. 159
Table 2.1: Conceptual Milestones in Social Capital Research………………………………… 27
Table 2.2: Summary of Key Empirical Findings in Social Capital Research……………… 28
Table 2.3: Comparison of Social Capital Approaches in Organizational Studies………29
Table 2.4: Conceptual Milestones in Organizational Capabilities Research……………. 54
Table 2.5: Summary of Key Empirical Findings in Organizational Capabilities Research…………………………………………………….………………………………………… 55
Table 4.1: Age Distribution of Sample…………………………………………………………………… 91
Table 4.2: Educational Distribution of Sample………………………………………………………. 91
Table 4.3: Gender Distribution of Sample……………………………………………………………… 91
Table 4.4: Demographic Distribution of Sample……………………………………………………. 92
Table 4.5: Measurement Interval One – Means, Standard Deviations, and Zero-Order Correlation Coefficients……………………………………………………. 101 Table 4.6: Measurement Interval Two – Means, Standard Deviations, and Zero-Order Correlation Coefficients……………………………………………………. 102 Table 4.7: Measurement Interval Three – Means, Standard Deviations, and Zero-Order Correlation Coefficients……………………………………………………. 103 Table 4.8: Confirmatory Factor Analysis Results for Comparative Social Capital
Measurement Models………………………………………………………………………… 111 Table 4.9: Discriminant Validity Analysis of Comparative Social Capital Factor
Structures…………………………………………………………………………………………… 111 Table 4.10: Regression Weights for Social Capital Measurement Model………………..114
Table 4.11: Standardized Total Effects for Social Capital Measurement Model…….. 115
xiii
Table 4.12: Summary of Model Fit Indices for Social Capital Measurement Model………………………………………………………………………….. 116
Table 4.13: Regression Weights for Capability Performance Measurement Model………………………………………………………………………….. 122
Table 4.14: Standardized Total Effects for Capability Performance Measurement Model………………………………………………………………………….. 123 Table 4.15: Summary of Model Fit Indices for Capability Performance Measurement Model………………………………………………………………………….. 124 Table 4.16: Confirmatory Factor Analysis Results for Comparative Capability
these reasons it is important to question both the nature of the relationships between
social capital and capability performance, as well as the patterns of relationships among
these constructs over time. Thus, this research also examines the following questions:
What impact does social capital emergence have on the longitudinal evolution of
organizational capabilities?
Do social capital and organizational capabilities co-evolve over time?
The next section specifies begins to identify the precise hypotheses associated with the
theoretical model to be specified and tested herein.
Dissertation Contributions and Practical Implications
We have indicated that this dissertation’s fundamental research question is:
‘How does social capital emergence influence the evolution of organizational
1 Theoretical exceptions include: Blyler & Coff (2003) who discuss the relationship between social capital,
dynamic capabilities, and the generation and appropriation of resulting rents; and Gooderham (2007) who addresses management-initiatives to enhance knowledge transfer within Multi-National Corporations using a social capital framework.
18
capabilities?’ Providing a conclusive answer to this question requires that we address
four key areas, as noted in the previous section: how social capital emerges and
develops over time; how this emergence influences the building of organizational
capabilities; whether social capital impacts capability evolution or change over time;
and, whether social capital and organizational capabilities longitudinally co-evolve.
Addressing these fundamental issues is therefore the terrain of this research project. To
do so we take a situated performance perspective (Haas & Hansen, 2005), as it focuses
on a pragmatic practice-based investigation (Bourdieu, 1990; Dewey, 1938) taking us
closer to the phenomena as they exist in the specific research context, and reducing the
conceptual distance between occurrence, observation and understanding. The benefits
of this orientation lie: first, in the treatment of capability evolution as being of value for
its contribution to creating reliable collaborative performance outcomes; second, in the
recognition that the value of social capital stems from when, whether and how it
contributes to the fitness of organizational capabilities; and third, in determining the
implications of early performance on the evolution of organizational capabilities and the
growth of social capital.
Opening the ‘black box’ of capability emergence is an important first step in
expanding our knowledge of the dynamics of organizational adaptation and evolution.
Unlike previous research which has focused more on post hoc examinations of
capabilities (for example, Montealegre, 2002; Tripsas & Gavetti, 2000), this work focuses
on the preliminary stage of capability development to attempt to shed new light on how
19
capabilities initially emerge. Management theory and application can clearly be
enhanced by examining the micro-foundations of capability change. Studying patterns
of social capital emergence offers a unique contribution to the understanding of how
capabilities evolve because it begins to untangle the causal factors that drive capability
change from a socialized perspective rather than an historical one based on the study of
positions, paths, and processes. Proponents in the social capital literature have asserted
the concept’s importance in generating performance outcomes, but we know little
about whether the causality of these arguments is appropriate or how the pattern of
influence occurs.
Apart from their theoretical novelty, the results of this research project hold
relevance to a practitioner audience interested in capabilities building. Here, the added
value to management practice stems from the potential development of intervention
mechanisms which would add some measure of control and predictability to capability
emergence. The ability to take action to encourage, stabilize, or discourage the
emergence of organizational capabilities via specific intervention mechanisms, provides
a powerful opportunity to maintain alignment between internal processes and
performance objectives. Offering the fields of organizational design and strategic
management the opportunity to intervene meaningfully would clearly enhance future
practice by increasing the alternatives available to control performance variation (for
example: encouraging emergence during product or process innovation cycles;
controlling emergence during production start-up cycles; discouraging emergence
20
during routine production cycles), beyond their current repertoire. By better
understanding the role that social capital plays in the emergence of organizational
capabilities we may open the door to a variety of intervention strategies amenable to
the specific context in which a given organization resides.
In conclusion, linking these distinct fields of thought in a longitudinal framework
illustrating their combined performance is a strong contribution in its own right.
However, connecting the performance implications resulting from mutual emergence
and co-evolution of social capital and organizational capabilities makes a potentially
significant leap forward. Therefore, understanding how social capital emerges and
organizational capabilities evolve is a worthwhile endeavor at this time, as it offers
organization scientists and managers the opportunity to take action in a deliberate,
purposeful, and timely fashion to encourage capability change and enhance
performance.
Organization of the Dissertation
This research develops and tests arguments which illustrate and advance the
current state of knowledge reflected in the relevant literatures; the structure of the
remainder of the thesis is as follows. Chapter two provides a comprehensive review of
the most relevant findings and conclusions contained in the primary bodies of literature
addressing social capital and organizational capabilities. The conceptual and intellectual
heart of this study is located in chapter three. Here, discussion centers on three core
21
areas: construct and theory development; introduction and elaboration of a conceptual
model; and restatement of the model’s central arguments in the form of testable
hypotheses.
Research design and research methodology are addressed in the fourth chapter,
which contains a description of the research site and the method of study. In addition,
this chapter includes specifics regarding the sampling parameters, the mixed method
survey-experimental approach, as well as the operationalization and measurement of
each of the primary constructs under study. Chapter five details the analytic approach
used in this research, and examines the results of these analyses. Findings of this study,
including an examination and interpretation of the results – their implications and
limitations, are presented and contributions to the literature discussed in the sixth
chapter. The seventh and final chapter summarizes this research and provides an
overview of the contributions and future directions made possible by this project.
22
Chapter Two: Literature Review
The social capital and organizational capabilities literature considered relevant
for this research project is reviewed herein; first from a conceptual perspective, and
later with the introduction of empirical contributions. The materials originate from two
distinct intellectual traditions; social capital derived from developments in the field of
sociology, and organizational capabilities from the advent of evolutionary economic and
later resource-based theorizing. Maintaining consistency with the central research
question driving this dissertation – ‘How does the emergence of social capital influence
the evolution of organizational capabilities?’, the concept of social capital will first be
considered, followed by an illustration of the foundational work as well as more
contemporary developments in the organizational capabilities literature. Intersections
between the two streams of theory, while rare, afford the opportunity to reflect on
potential similarities between the concepts, and provide a foothold for further
theorizing in support of the third chapter. Given the already large, and constantly
expanding bodies of research associated with these two concepts, the aim here is not to
provide the reader with a general understanding of each field, but rather with a
comprehensive knowledge of areas which apply directly to this project.
Social Capital Literature Review: Conceptual, Theoretical, and Empirical
In general, social capital has been defined, discussed, and considered from a
plethora of perspectives, and with a multitude of intents (Adler & Kwon, 2002). Consider
23
Adler and Kwon’s (2002) review of the various usages of social capital, and how the
construct has been construed across multiple disciplines and levels of analysis. In the
broader social capital literature, terms such as cultural capital and relational capital have
entered the social capital lexicon (Bourdieu, 1986, 1990; Putnam, 1995), and distinctions
between the public versus private value of social capital have been considered (Burt,
Ghoshal, 1998). This holistic perspective is the one that best informs our definition of
social capital as “the sum of the actual and potential resources embedded within,
available through, and derived from the network of relationships possessed by an
individual or social unit” which thus “comprises both the network and the assets that
may be mobilized through that network” (Nahapiet & Ghoshal, 1998: 243). Because this
definition considers social capital from a comprehensive perspective, the literature
introduced here will incorporate both orientations as well.
In Table 2-3 the essence of each conceptualization of social capital is illustrated
for comparative purposes, however, it is worth mentioning that variance among
scholars within each major division does exist. The central point illustrated in Table 2-3
lies in the distinctions between how social capital is constituted, valued and configured,
across each of the three perspectives. While each of these dimensions will be
considered in depth, it is worth noting a pair of critical points of agreement among the
25
three approaches. First, there is generally agreement recognizing the generative nature
of social capital as an enduring social resource (Adler & Kwon, 2002; Burt, 2000; Moran,
2005). In contrast to other types of resources whose values tend to diminish with use,
social capital is considered to be generative in that its value is presumed to increase
with constructive use (obviously decreasing in value to the degree that destructive
conflict arises among linked members). The more a given pattern of relationships is
relied upon, the more likely that trust, mutual respect, and social solidarity will develop
and persist between network members, as “most behavior is closely embedded in
networks of interpersonal relations” (Granovetter, 1985: 504)3. This point, that social
capital is a generative resource within organizations, is a critical attribute of social
capital and an incredibly important consideration in the study of the micro-foundations
of organizational capabilities within the context of organizations, a point to which we
return at the conclusion of the chapter.
A second point of agreement lies in universal treatment of the term
embeddedness. Although authors typically precede embeddedness with a qualifier, such
as structural, relational, or cognitive, until recently it was attributed only a vague
definition referring broadly to a process in which the network of social relations come to
pattern the exchanges among actors, such that it becomes increasingly difficult to
3 From a structural perspective, this argument holds in that as brokerage opportunities increase, the value
to the broker’s position would similarly increase due to an increased dependence on the broker by the alters (or information seekers). However, the value of information or knowledge – as distinct from position – may decrease as weaker ties (commonly associated with diverse information) become stronger (or more closely linked) due to an increasing frequency in the number of interactions.
26
separate the actions of the individual from the social context in which they occur
(Granovetter, 1985; Uzzi, 1997). Increasingly however, researchers including those
interested in social capital have recognized the need to qualify the nature of
embeddedness, and their interpretation of it, by situating both the actor and pattern of
social relations in a specific structural or institutional context (Baum & Dutton, 1996;
by some, toward creating a comprehensive understanding of social capital, based on an
integrative perspective, lends support to the choice of definition used in this
dissertation, that social capital is “the sum of the actual and potential resources
embedded within, available through, and derived from the network of relationships
possessed by an individual or social unit” which thus “comprises both the network and
the assets that may be mobilized through that network” (Nahapiet & Ghoshal, 1998:
243). In this paper, the general term embeddedness is taken as referring to the
patterned nesting of an individual’s activities within the situated context of the group,
but which requires substantive qualification to be meaningful (Granovetter, 1985;
Moran, 2005)4. It is from this perspective, one that merges integrative and situated
approaches, that we consider the recent developments in the social capital literature.
4 Here, we take an approach consistent with that of Oliver (1996:164) in which embeddedness was
qualified as “institutional embeddedness” and contextualized as a firm level construct defining the pattern of activity between firms and their institutional context.
27
Au
tho
rsA
rtic
le T
itle
Lev
el o
f A
na
lysis
Ind
ep
en
de
nt
Vari
ab
les
De
pe
nd
en
t V
ari
ab
les
Majo
r F
ind
ing
s a
nd
Co
nc
lus
ion
s
Gra
no
vetter
(1985)
Eco
no
mic
action a
nd s
ocia
l str
uctu
re:
The p
rob
lem
of
em
beddedness
Indiv
idual; D
yad
Th
is p
ap
er
co
nce
rns the e
xte
nt
to w
hic
h e
co
nom
ic
actio
n is e
mb
ed
de
d in
str
uctu
res o
f so
cia
l
rela
tio
ns, in
mo
de
rn in
du
str
ial so
cie
ty. U
nder-
and
overs
ocia
lize
d a
cco
un
ts a
re p
ara
do
xic
ally
sim
ilar
in th
eir n
egle
ct
of
ong
oin
g s
tru
ctu
res o
f socia
l
rela
tio
ns. A
so
ph
istica
ted
acco
un
t o
f e
co
no
mic
actio
n m
ust co
nsid
er
its e
mb
ed
de
dn
ess in
such
str
uctu
res.
Bourd
ieu (
1986)
Form
s o
f C
apital
Indiv
idual; S
ocie
tal
Dis
cusse
s thre
e f
orm
s o
f capita
l: e
conom
ic,
so
cia
l, a
nd c
ultu
ral. W
here
so
cia
l ca
pita
l is
the
agg
reg
ate
of
the
actu
al o
r p
ote
ntia
l re
so
urc
es
wh
ich a
re lin
ke
d to p
osse
ssio
n o
f a
dura
ble
netw
ork
re
latio
nsh
ips w
hic
h p
rovid
e e
ach o
f its
me
mb
ers
with
th
e b
ackin
g o
f th
e c
olle
ctivity-
ow
ned
capita
l, a
"cre
de
ntia
l" w
hic
h e
ntitle
s t
hem
to c
redit, in
th
e v
ariou
s s
ense
s o
f th
e w
ord
.
Cole
man (
1988)
Socia
l ca
pita
l in
the c
reation o
f
hum
an c
apital
Indiv
idua
l; G
roup; C
om
mu
nity
Con
ce
pt
of
so
cia
l ca
pita
l is
in
tro
duce
d a
nd
illu
str
ate
d, its f
orm
s a
re d
escrib
ed
, th
e s
ocia
l
str
uctu
ral cond
itio
ns u
nd
er
wh
ich
it arises a
re
exa
min
ed
. T
he c
once
ptio
n o
f so
cia
l ca
pital a
s a
resourc
e f
or
actio
n in
tro
duces s
ocia
l str
uctu
re into
the r
atio
na
l a
ctio
n p
ara
dig
m. T
he r
ole
of
clo
su
re in
the s
ocia
l str
uctu
re in
fa
cili
tatin
g s
ocia
l capita
l is
describ
ed
.
Nahapie
t &
Ghoshal (1
998)
Socia
l capita
l, inte
llectu
al captial, a
nd
the o
rganiz
ational advanta
ge
Indiv
idua
l and G
roups w
ithin
Org
aniz
ations a
nd
Institu
tions
So
cia
l C
apita
lIn
telle
ctu
al C
apita
l
Th
e a
uth
ors
arg
ue:
so
cia
l ca
pita
l fa
cili
tate
s t
he
cre
ation o
f n
ew
in
telle
ctu
al ca
pita
l; o
rgan
izatio
ns,
as in
stitu
tio
nal se
ttin
gs, are
co
nd
uciv
e to
th
e
develo
pm
ent
of
hig
h le
ve
ls o
f so
cia
l ca
pital; a
nd it
is b
eca
use
of
mo
re d
en
se
so
cia
l ca
pita
l firm
s
have a
n a
dva
nta
ge
ove
r m
ark
ets
in
cre
ating a
nd
sh
aring in
telle
ctu
al ca
pita
l.
Adle
r &
Kw
on (
2002)
Socia
l capita
l: P
rospects
for
a n
ew
constr
uct
Indiv
idual
So
cia
l S
tru
ctu
re; M
otivation;
Op
po
rtu
nity;
Ab
ility
Va
lue C
reatio
n
Cla
rifie
s t
he s
ocia
l ca
pita
l a
nd
help
assess its
utilit
y fo
r org
an
iza
tio
na
l th
eory
. S
ynth
esiz
es
theo
retica
l re
se
arc
h u
nde
rta
ke
n in
va
rious
dis
cip
lines a
nd
de
ve
lop a
co
mm
on c
onceptu
al
fram
ew
ork
tha
t id
en
tifie
s the
so
urc
es,
be
ne
fits
,
risks, an
d c
ontin
ge
ncie
s o
f so
cia
l ca
pita
l.
Ibarr
a, K
ilduff
& T
sai (2
00
5)
Zoom
ing in a
nd o
ut: C
onnecting
indiv
iduals
and
co
llectivitie
s a
t th
e
frontiers
of
org
aniz
ational netw
ork
rese
arc
h
Indiv
idual; O
rgan
izatio
n
Th
e a
uth
ors
arg
ue f
or
zo
om
ing b
ack a
nd f
ort
h
betw
een
in
div
idua
l a
nd
co
llective le
ve
ls o
f
ana
lysis
, to
co
nsid
er
how
acto
rs m
ay
benefit
or
detr
act
fro
m the
co
llective
go
od
. T
he a
uth
ors
co
nsid
er
how
in
div
idua
l co
gn
itio
ns a
bo
ut
sh
ifting
netw
ork
co
nn
ectio
ns a
ffe
ct, a
nd a
re a
ffe
cte
d b
y,
larg
er
so
cia
l str
uctu
res.
Inkpen &
Tsang (
2005)
Socia
l capita
l, n
etw
ork
s,
and
kn
ow
ledge tra
nsfe
rO
rganiz
ation;
Inte
rorg
aniz
atio
nS
ocia
l C
apita
l; N
etw
ork
Typ
eK
now
ledg
e T
ransfe
r
Usin
g a
so
cia
l capita
l fr
am
ew
ork
, th
e a
uth
ors
identify
str
uctu
ral, c
ogn
itiv
e, a
nd
re
latio
na
l
dim
ensio
ns f
or
thre
e n
etw
ork
typ
es. T
hey
link
so
cia
l capita
l d
ime
nsio
ns t
o t
he
co
nd
itio
ns t
ha
t
facili
tate
know
ledg
e tra
nsfe
r. T
he a
uth
ors
pro
pose
a s
et o
f co
nd
itio
ns tha
t p
rom
ote
kn
ow
ledge
tra
nsfe
r fo
r th
e d
iffe
ren
t netw
ork
typ
es.
Oh, Labia
nca &
Chung (
2006)
A m
ultile
vel m
odel of
gro
up s
ocia
l
capital
Gro
up
s (
intr
a/in
ter)
Gro
up S
ocia
l C
apita
l C
ond
uits;
Gro
up's
Socia
l C
apita
l R
esourc
es
Gro
up
Pe
rfo
rma
nce
; In
div
idua
l
Gro
wth
; S
atisfa
ctio
n
Th
e a
uth
ors
intr
od
uce
th
e c
once
pt of
gro
up s
ocia
l
ca
pita
l--t
he s
et o
f re
so
urc
es m
ade a
vaila
ble
to a
gro
up th
rou
gh m
em
bers
' so
cia
l re
latio
nship
s
within
th
e s
ocia
l str
uctu
re o
f th
e g
roup
and in
the
bro
ader
form
al a
nd
in
form
al str
uctu
re o
f th
e
org
aniz
atio
n. T
hey
arg
ue tha
t g
rea
ter
gro
up s
ocia
l
ca
pita
l le
ad
s to g
rea
ter
gro
up e
ffe
ctive
ness a
nd
diffe
ren
t co
nd
uits thro
ug
h w
hic
h r
eso
urc
es f
low
.
Table 2.1 Conceptual milestones in social capital research
28
Table 2.2 Summary of key empirical findings in social capital research
Au
tho
rsA
rtic
le T
itle
Em
pir
ical S
ett
ing
Lev
el o
f A
naly
sis
Meth
od
of
An
aly
sis
Ind
ep
en
den
t V
ari
ab
les
Dep
en
den
t V
ari
ab
les
Majo
r F
ind
ing
s a
nd
Co
nclu
sio
ns
Burt
(1997)
The c
ontingent valu
e o
f socia
l
capital
Quantita
tive f
ield
surv
ey
of
two
sam
ple
s:
(1)
170 m
ale
senio
r
managers
(A
merican
ele
ctr
onic
s c
om
ponents
in
1989)
for
baselin
e c
om
para
tive
data
; (2
) re
analy
sis
of
a
pre
vio
us "
bankin
g"
data
set
deta
iled in B
urt
(1992)
Indiv
idual
Data
colle
cte
d u
sin
g f
ield
surv
ey
instr
um
ent and n
etw
ork
based n
am
e-g
enera
tor;
Analy
sis
based o
n L
ogit
Pro
babili
ty E
stim
ate
s
Num
ber
of
Manag
erial P
eers
;
Com
petitive P
ressure
s a
mong
Peers
; Legitim
acy o
f P
ositio
n
Valu
e o
f an indiv
idual's
str
uctu
rally
defined s
ocia
l
capital
Str
uctu
ral ecolo
gy o
f socia
l capital describes the
valu
e o
f socia
l capital to
indiv
iduals
is c
ontingent
on the n
um
ber
of
people
doin
g the s
am
e w
ork
.
Info
rmation a
nd c
ontr
ol benefits
of
bridgin
g t
he
str
uctu
ral hole
s t
hat constitu
te s
ocia
l capital are
especia
lly v
alu
able
to those w
ith f
ew
peers
,
because these m
anagers
do n
ot have the
legitim
acy p
rovid
ed b
y n
um
ero
us p
eople
doin
g t
he
sam
e type o
f w
ork
.
Uzzi (1
997)
Socia
l str
uctu
re a
nd
com
petition in inte
rfirm
netw
ork
s: T
he p
ara
dox o
f
em
beddedness
Eth
nogra
phic
stu
dy o
f 23 b
ett
er-
dre
ss f
irm
s in the N
ew
York
City
appare
l in
dustr
y.
Org
aniz
ation
Data
colle
ction a
nd a
naly
sis
consis
tent w
ith g
rou
nded
theo
ry a
ppro
ach
.
Socia
l S
tructu
ral A
nte
cedents
;
Tru
st; F
ine-g
rain
ed
Info
rmatio
n; and J
oin
t P
roble
m-
solv
ing A
rrangem
ents
De
gre
e o
f E
mbeddedness
(Over
or
Under
Em
bedded in
Ne
twork
of
Firm
s)
Identifies t
he c
om
ponents
of
em
bedded
rela
tionship
s a
nd the d
evic
es b
y w
hic
h
em
beddedness s
hapes o
rganiz
ational outc
om
es.
Fin
din
gs s
uggest
that em
beddedness is a
logic
of
exchange that
pro
mote
s e
conom
ies o
f tim
e,
inte
gra
tive a
gre
em
ents
, and c
om
ple
x a
dapta
tion.
Em
beddedhess c
an m
ake f
irm
s v
uln
era
ble
to
exogenous s
hocks o
r in
sula
te them
fro
m
info
rmation t
hat beyond their n
etw
ork
.
Tsai &
Ghoshal (1
998)
Socia
l capital and v
alu
e
cre
ation: T
he r
ole
of
intr
afirm
netw
ork
s
Managers
(3 p
er
unit)
from
one
multin
ational ele
ctr
onic
s
com
pany
with 1
5 d
istinct
busin
ess u
nits w
ere
surv
eye
d
usin
g a
mail
questionaire
consis
tent w
ith a
fie
ld s
tudy
appro
ach.
Intr
a-o
rganiz
ation; S
trate
gic
Busin
ess U
nit (
SB
U)
Con
vers
iona
l of
rela
tiona
l data
into
dya
dic
fro
m u
sin
g M
ultip
le
Regre
ssio
n Q
uadra
tic
Assig
nm
ent P
rocedure
s
(MR
QA
P),
follo
we
d b
y data
analy
sis
usin
g L
ISR
EL 8
str
uctu
ral e
quation m
odelin
g.
Socia
l C
apital; R
esourc
e
Exchan
ge a
nd C
om
bin
ation
Valu
e C
reation
The a
uth
ors
exam
ine t
he r
ela
tionship
s a
mong the
str
uctu
ral, r
ela
tional, a
nd c
ognitiv
e d
imensio
ns o
f
socia
l capital and b
etw
een those d
imensio
ns a
nd
patt
ern
s o
f re
sourc
e e
xchange a
nd p
roduct
innovation.
The s
tructu
ral dim
ensio
n a
nd the
rela
tional dim
ensio
n,
were
sig
nific
antly r
ela
ted to
the e
xte
nt
of
inte
runit r
esourc
e e
xchange, w
hic
h
had a
sig
nific
ant eff
ect
on p
roduct
innovation.
Hansen (
1999)
The s
earc
h-t
ransfe
r pro
ble
m:
The r
ole
of
weak tie
s in s
haring
know
ledge a
cro
ss o
rganiz
ation
subunits
Uses n
etw
ork
stu
dy o
f 120
pro
duct develo
pm
ent pro
jects
undert
aken b
y 41 d
ivis
ions in a
larg
e e
lectr
onic
s c
om
pany.
Pro
ject (B
usin
ess U
nit le
vel)
Data
first an
aly
zed u
sin
g
UC
INE
T IV
, fo
llow
ed b
y
inte
gra
tio
n into
haza
rd r
ate
models
, w
hic
h w
ere
ana
lyzed
usin
g M
axim
um
Lik
elih
ood
Estim
atio
n in the T
DA
sta
tistical pro
gra
m.
Inte
runit T
ie W
eakness;
Nonco
difie
d K
now
ledge;
Dependent K
now
ledge
Pro
ject C
om
ple
tion T
ime
This
paper
com
bin
es t
he c
oncept
of
weak tie
s
from
socia
l netw
ork
researc
h a
nd the n
otion o
f
com
ple
x k
now
ledge t
o e
xpla
in the r
ole
of
weak
ties in s
haring k
now
ledge. F
indin
gs s
how
that
weak inte
runit t
ies h
elp
a p
roje
ct
team
searc
h f
or
usefu
l know
ledge in o
ther
subunits b
ut
impede the
transfe
r of
com
ple
x k
now
ledge, w
hic
h r
equire
str
ong tie
s b
etw
een the p
art
ies. H
avin
g w
eak
inte
runit tie
s s
peeds u
p p
roje
cts
when k
now
ledge
is n
ot com
ple
x b
ut
slo
ws t
hem
dow
n w
hen
know
ledge is h
ighly
com
ple
x.
Levin
& C
ross (
2004)
The s
trength
s o
f w
eak t
ies y
ou
can tru
st: T
he m
edia
ting r
ole
of
trust in
eff
ective k
now
ledge
transfe
r
Tw
o-p
hase q
uantita
tive f
ield
surv
ey
data
colle
ction f
rom
118
respondents
work
ing o
n
pro
jects
and in p
roje
ct
team
s in
thre
e o
rganiz
ations a
cro
ss
thre
e s
ecto
rs (
Am
erican
Pharm
aceutical; B
ritish
Bankin
g;
Canadia
n O
il and
Gas).
Indiv
idua
l; D
yadic
Ord
inary
Least S
quare
s
Regre
ssio
n o
f data
colle
cte
d
sole
ly f
rom
the p
resp
ective o
f
the k
now
ledg
e s
eeker
Tie
Str
ength
; C
om
pete
nce-
based T
rust; B
ene
vole
nce-
based T
rust; T
acitness o
f
Know
ledge
Re
ceip
t of
Usefu
l K
now
ledge
The a
uth
ors
pro
pose a
nd t
est a m
odel of
dya
dic
know
ledge e
xchange. T
he lin
k b
etw
een s
trong
ties a
nd r
eceip
t of
usefu
l know
ledge w
as
media
ted b
y c
om
pete
nce-
and b
enevole
nce-
based t
rust. C
ontr
olli
ng f
or
the tw
o tru
stw
ort
hin
ess
dim
ensio
ns,
the s
tructu
ral benefit
of
weak t
ies
em
erg
ed. F
indin
gs s
uggests
weak t
ies p
rovid
e
access t
o n
onre
dundant in
form
ation.
Com
pete
nce-
based t
rust w
as im
port
ant fo
r th
e r
eceip
t of
tacit
know
ledge.
Mora
n (
2005)
Str
uctu
ral vs. re
lational
em
beddedness: S
ocia
l capital
and m
anagerial perf
orm
ance
Based o
n a
sam
ple
of
120
pro
duct and s
ale
s m
anagers
in
a F
ort
une 1
00 p
harm
aceutical
firm
.
Indiv
idual
Da
ta a
naly
ze
d u
sin
g S
TA
TA
6.0
multiv
ariate
re
gre
ssio
n to
test hyp
oth
eses.
Socia
l C
apital
Manag
erial S
ale
s
Perf
orm
ance; M
anageria
l
Innovation P
erf
orm
ance
This
paper
exam
ines t
he im
pact of
socia
l capital
on m
anagerial perf
orm
ance. T
wo d
imensio
ns o
f
socia
l capital are
com
pare
d—
str
uctu
ral
em
beddedness a
nd r
ela
tional em
beddedness.
Evid
ence indic
ate
s b
oth
ele
ments
influence
managerial perf
orm
ance. S
tructu
ral pla
ys a
str
onger
role
in e
xpla
inin
g m
ore
routine, execution-
oriente
d tasks, w
here
as r
ela
tional pla
ys a
str
onger
role
in e
xpla
inin
g n
ew
, in
novation-o
riente
d tasks.
Balk
undi &
Harr
ison (
2006)
Tie
s, le
aders
, and tim
e in
team
s: S
trong infe
rence a
bout
netw
ork
str
uctu
re's
eff
ects
on
team
via
bili
ty a
nd p
erf
orm
ance
Meta
-analy
sis
conta
inin
g 3
7
stu
die
s w
ith 6
3 e
ffect siz
es
involv
ing 3
098 team
s.
Indiv
iduals
in G
roup
s; G
roup
Meta
-an
aly
sis
of
stu
die
s b
ase
d
on thre
e c
rite
ria: (1
) te
am
s o
f
adults in n
atu
ral w
ork
ing
environm
ent; (
2)
opera
tio
naliz
ed info
rmal
netw
ork
s u
sin
g s
ocia
l n
etw
ork
meth
odo
logy; (3
) o
utc
om
e
variab
le h
ad to b
e tea
m le
vel.
Eff
ect siz
es o
f: D
ensity-
Perf
orm
ance
Rela
tio
nship
;
Density-
Via
bili
ty R
ela
tionship
;
Tie
Conte
nt-
Team
Outc
om
e
Rela
tio
nship
; C
entr
alit
y-
Perf
orm
ance
Rela
tio
nship
;
Modera
tin
g E
ffects
of
Tim
e
Team
Task P
erf
orm
ance;
Team
Via
bili
ty
A m
eta
-analy
sis
of
team
s in n
atu
ral conte
xts
suggests
that te
am
s w
ith d
ensely
configure
d
inte
rpers
onal ties a
ttain
better
team
task
perf
orm
ance a
nd v
iabili
ty.
Team
s w
ith leaders
who a
re c
entr
al in
the t
eam
s’ in
tragro
up n
etw
ork
s
and team
s that are
centr
al in
their inte
rgro
up
netw
ork
tend to p
erf
orm
bett
er.
Team
s w
ith
densely
configure
d inte
rpers
onal ties a
ttain
better
team
task p
erf
orm
ance a
nd v
iabili
ty.
29
Table 2.3 Comparison of social capital approaches in organizational studies
Structural Holes Theory
Relational Network Theory
Integrated Social Capital Theory
Definition “Structural holes are thus an opportunity to broker the flow of information between people, and control the projects that bring people form opposite sides of the hole” (Burt, 2000: 353 emphasis in original).
“Features of social organization such as networks, norms, and social trust that facilitate coordination and cooperation for mutual benefit” (Putnam, 1995: 67).
“The sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit” which thus “comprises both the network and the assets that may be mobilized through that network” (Nahapiet & Ghoshal, 1998: 243).
Emphasis Individual or focal actor as broker may benefit from relative position in a network, and linkage patterns among others.
System benefits attributable to a variably closed system of relations among nearby network actors.
Balances both individual and collective considerations, where brokerage and closure are equally relevant.
Level of Analysis
Generally individual or ego-centric, but can be applied at many levels based on researcher specification.
Whole network, but network may be conceptualized at many levels based on researcher specification.
Ego-centric or whole network are equally applicable at many levels based on researcher specification.
Constitution Emphasis on network structure and the structural embeddedness of among actors.
Emphasis on relational embeddedness and quality of relationships between actors.
Emphasis on structural, relational and cognitive embeddedness among actors.
Value Private value based on opportunity for focal actor to benefit from network position and brokerage of unique connections (tertius gaudens).
Public value based on mutuality of linkages creating shared access to information, influence, and social status.
Private and public value relevant, contingent on contextually-specific demands. Possible to consider from a variety of perspectives.
Configuration Network structure leads to unique patterns of association, creating network holes. Lack of structural equivalence allows actor to uniquely bridge gaps in network.
The content quality of linkages within the network structure creates closure, which results in bonding among actors in social network.
Integrates structural embeddedness as context, relational embeddedness as content of network, allowing consideration of both bridging and bonding activities.
30
The Constitution of Social Capital
“What constitutes social capital?” has been a hotly debated topic within
organizational studies (Adler & Kwon, 2002; Burt, 2000). Early writing addressing social
capital from a societal perspective suggested that it is a convertible currency accruing to
people with networks composed of strong multi-directional relationships which
developed over time, providing the basis for trust, cooperation, coordination and
collective action (Bourdieu, 1986). In the context of interpersonal networks, social
capital was seen as a credential; to be used in place of traditional forms of capital to
appropriate benefits among networks of relations and acquaintances (Bourdieu, 1986).
While removed from an organizational context, this early work continues to impact our
current conception of social capital, especially in contexts where organizations are seen
as communities or networks of practice (for a review of this field, consider Davenport &
Hall, 2002). Here, social capital is presumed to convey social status, demonstrate
reputation quality through membership or affiliation with high status others, and thus
provide benefits to the holder (Burt, 1992). Differences persist with respect to the scope
of what constitutes social capital, and how many dimensions should be considered
2002; Tsai & Ghoshal, 1998). This unified perspective is an essential dimension of an
integrative approach to understanding how social capital contributes to the emergence
of organizational capabilities.
5 In this regard consider the implications of a situation in which an individual with many weak ties brings
much needed and otherwise unavailable information to bear on a group project. Here we may be able to examine the individual benefits (private) accruing to status and career advancement, however it is equally likely that we may witness group learning (collective) as new knowledge is received and integrated, or even project-level outcomes (public) in terms of innovation success. All may be equally present, yet the focus on specific outcomes (or dependent variables) tends to censor the ways in which value is construed.
40
The Configuration of Social Capital – Does Configuration Matter?
A final point of differentiation in the organizational social capital literature
relates to the configuration or architecture of the social networks inhabited by
organization members. While two distinct theories proposing fundamentally divergent
conceptions of network architecture have taken hold – the first emphasizing structural
holes (Burt, 1992, 1997) in the network and the other emphasizing network closure
(Coleman, 1988; Portes, 1998) – there is growing recognition that these may be
complementary rather than incommensurable (Adler & Kwon, 2002; Burt, 2000;
Nahapiet & Ghoshal, 1998). Moreover, growing reconciliation of the complementarities
of the two has lead authors to consider the importance of a unified perspective such
that “closure provides social capital’s cohesiveness benefits within an organization or
community; structural holes in the focal actor’s external linkages provide cost-effective
resources for competitive action” (Adler & Kwon, 2002: 25), where the value of
configuration is contingent on the task and contextual environment confronting the
actor.
A contextually-specific or a situated approach, where the implications of social
capital are contingent on the complementarity among actors, network configuration,
and task environment is well suited to this research project because it facilitates the
incorporation of situation-specific considerations which add richness and realism to the
organizational context under study. In this regard, four primary considerations have
been demonstrated to characterize interactions in organizational contexts (Nahapiet &
41
Ghoshal, 1998). The first among these is the impact of time, where social capital
depends on stability and continuity of social structure (Bourdieu, 1986; Coleman, 1988).
Second, interdependence among actors is essential. Under conditions characterized by
mutual interdependence the importance of social capital is driven up, while erosion is
believed to occur as dependence declines (Coleman, 1990). A third factor is social
interaction, where social capital requires continued social interaction among tied-
partners or maintenance of relationships to maintain the quality of network ties. Here,
social interaction is a precondition for development and maintenance of dense, strong
social capital (Adler & Kwon, 2002; Bourdieu, 1986), regardless of whether ties are
considered predominantly instrumental (task oriented), expressive (socially supportive),
or comprehensive in nature (Oh et al., 2004). Closure – understood to mean the extent
to which network members’ contacts are themselves connected – a final characteristic
of formal organizations, has been suggested to improve the cognitive and relational
dimensions of social capital by bonding the members to one another with strong
relationship ties within densely configured networks (Adler & Kwon, 2002; Coleman,
1988; Oh et al., 2006). Within an organizational context closure is naturally occurring,
based primarily on membership within the socially constructed boundaries of the
organization (Kogut & Zander, 1996), but may also occur across organizational
boundaries based on structural embeddedness and common strong ties among actors
(Uzzi, 1997). Although distinct in nature, each of these four characteristics illustrates the
42
need to undertake research from a situated perspective, where fit between
organizational context and social capital configuration is emphasized.
Bridging Ties, Bonding Ties or Both
The utility of social capital is contingent on the fit between context factors and
its configuration within the organization. The ability to benefit from potential increases
in the efficiency of action, such as improved information transfer and diffusion through
weak ties (Burt, 1992), personal and career advancement (Burt et al., 2000;
Sproull, 2004; Nebus, 2006), are representative of the bridging configuration
perspective (Burt, 2000; Oh et al., 2006). In contrast, the ability to benefit from
increases in the effectiveness of action, such as through cooperative behaviors that
support coordinated or improvised learning (Vera & Crossan, 2005), innovation (Grant,
1996; Kogut & Zander, 1992), or rich information exchange (Hansen, 1999, 2002), is
deeply reflective of the bonding configuration perspective (Burt, 2000; Oh et al., 2006)6.
Given the divergence between the perspectives, in combination with the recognition
that both types of relationships are generally needed within organizations, it is not
surprising to see reconciliation of the two views developing in the field (Nahapiet &
Ghoshal, 1998; Oh et al., 2004; Oh et al., 2006). Some have even gone so far as to
6 Many in depth reviews of the construal of bonding (closure) and bridging (brokerage) relationships have
been constructed from a variety of perspectives. For a more thorough review consider any of these examples (Burt, 2000; Lin, 1999; Davenport & Snyder, 2005; Portes, 1998; Raider & Krackhardt, 2002).
43
endorse the value of “dual network” architectures in which weak external ties are
bridged with strongly bonded internal ties to support innovation capacity (Capaldo,
2007).
Similarly, Oh et al. have suggested that organizations could achieve an optimal
network configuration, where “[t]he optimal [configuration] profile would be a group
where there is moderate closure within the group, group’s formal and informal
leadership roles are either fulfilled by the same person or by closely connected
individuals, the formal leader has close connections to each of the group’s subgroups,
various group members have nonredundant external ties to a diverse range of other
groups in the organization, and members have ties to influential dominant coalition
members whom they can count on for political support as needed” (2006: 578).
Consistent with Oh et al. (2006), the assertion here is that integrating both the bridging
and bonding perspectives is necessary to properly capture the implications of structural,
cognitive, and relational embeddedness, reflecting the value of configuration as
contingent on the task and contextual environment confronting the actor. In contrast
however, we avoid asserting or endorsing an archetypal configuration, and instead
suggest that an optimal configuration of ties will result as a product of perfect fit
between organizational context and the social capital configuration7.
7 It would seem here that a claim of “optimal configuration profile” presumes a static environment, and a
retrospective point of view. Since these are neither present nor relevant to the underlying pragmatic or situated perspective in which we have already underscored the implications of time, interdependence, social interaction, and closure, this point of departure is explicitly recognized.
44
Implications of Findings
The literature reviewed in this section spans nearly 25 years, and covers a wide
variety of perspectives and orientations. Its relevance however, has been established by
demonstrating how this varied body of literature contributes to an integrated theory of
social capital in organizations, a small but growing body of research. Differences in
terms of the constitution, value, and configuration of social capital lead to the assertion
that an integrative approach affords an enlarged recognition of social capital within an
organizational context, as it explicitly recognizes the implications of both network
structure and relationship quality. Further, the inclusion of cognitive considerations
adds an important degree of richness overlooked by alternate approaches. In
conclusion, the combined implications of structural, cognitive, and relational
embeddedness capture an awareness of the potential variations in the complexity of
social interactions between individuals and within social systems. The notion that the
constitution, value, and configuration of social capital is nested within contextually
specific settings, demonstrates the importance of adopting a pragmatic or situated
perspective to better understand the implications of social capital emergence on the
evolution of organizational capabilities.
Organizational Capabilities: An Organizational Theory Approach
As noted earlier, an organizational capability is defined here as a “collections of
routines that, together with their implementing input flows, confer upon an
45
organization’s management a set of decision options for producing significant outputs of
a particular type” (Winter, 2003: 991), which at their essence are “socially complex
routines that determine the efficiency with which firms physically transform inputs into
outputs” (Collis, 1994: 145). The advent of organizational capabilities was born of the
evolutionary economic theory perspective first articulated by Nelson and Winter (1982).
Although early variations in how the concept of capabilities was defined and used
served to obscure the exact nature of the term – often using it interchangeably with
routines, skills and capacities for action at various levels of analysis (Amit & Schoemaker,
1993; Cohen et al., 1996; Nelson & Winter, 1982) – more contemporary work in the field
has focused on delineating and differentiating organizational capabilities from other
forms of skill, routine, or collective action (Becker, Lazaric, Nelson, & Winter, 2005; Dosi
et al., 2001).
The literature introduced in support of this dissertation focuses explicitly on the
micro-foundations of organizational capabilities, dynamic and otherwise; recognizing
that the notions of individual skills and organizational routines are complementary,
organizational capabilities are argued to be distinct in nature, scope and impact on
organization performance outcomes as captured in our definition. For the purpose of
this research, routines pertain exclusively to the individual level of analysis, while
capabilities are conceptualized at the level of the group or social collective (Helfat et al.,
2007; Helfat & Peteraf, 2003). Here, the organizational value of routines and capabilities
– the former performed by the individual and the latter performed in combination by
46
groups and social collectives (Nelson & Winter, 1982) – rests predominantly on their
ability to shape, direct, and organize the behaviors of organizational participants in a
deliberate, consistent and predictable manner (Danneels, 2002; Dosi et al., 2001;
Winter, 2003). The notion that theories dealing with the development of organizational
capabilities ought to be grounded in a micro-foundational understanding is a broad and
Zuckerman, 2001). Similarly, network connectedness, which connotes “the extent to
which members of the network are linked to each other” (Tichy & Fombrun, 1979: 928),
and network centrality – or the extent to which the actor in a network is interconnected
with other relationships in the network (Raider & Krackhardt, 2002) – have been shown
to improve access to valued information and resources (Burt, 1997; Freeman, 1979;
Hansen, 1999). A further structural consideration that has also received considerable
attention in the literature focuses on issues of structural equivalency of networks (Burt,
1997). Structural equivalence speaks to the extent to which network members reside in
similar functional or network positions (Brass et al., 2004), and can be seen to influence
69
attitude formation and contagion among equivalent members (Burt, 1992), while
increasing confirmatory or redundant information benefits (Burt, 1997). Although
theoretically distinct from other constructs such as group cohesion or network
connectedness, structural equivalence has been implicated in increasing information
transmission and knowledge sharing among members and across networks (Balkundi &
Harrison, 2006; Burt, 1997).
Therefore, for the purposes of this dissertation social capital is presumed to
enhance the potential emergence of organizational capabilities to the degree that
network structures support access to varied and diverse sources of information, as well
as the transmission and integration of this information among organizational
participants. In this case, each organization member should appear both deeply
connected and structurally equivalent to the other members inside the organization,
thus members should be well-embedded structurally throughout the group network. As
a result:
H1a: Increasing structural embeddedness enhances the emergence of social capital.
Embeddedness within the Cognitive dimension of Social Capital
The nature of cognitive embeddedness, despite having gone unspecified in much
of the organizational social capital literature, reflects the extent to which a collective
70
cognitive schema is present between individuals in a social network8. The nature of
cognitive embeddedness is akin to the idea of a collective mind which is “manifest when
individuals construct mutually shared fields … that emerges during the interrelating of
an activity system” (Weick & Roberts, 1993: 365); or the notion of a collectively-held
knowledge code which “affects the beliefs of individuals, even while it is being affected
by those beliefs” (March, 1991: 75). These examples emphasize the patterned shaping
of processes that occur during task-performances by individuals and groups situated in
specific contexts (Grant, 1996), recognizing the prevalence of bounded rationality and
the implications of the boundaries themselves as situated in a specific environment
(Haas & Hansen, 2005).
Applying the cognitive dimension of social capital theory to organizational
settings, research has predominantly focused on the role of resources providing shared
representations and systems of meaning (Nahapiet & Ghoshal, 1998); shared narratives
within networks of practice (Brown & Duguid, 2000; Orr, 1996; Wasko & Faraj, 2005);
and the potential for routines to serve as repertoires for collective practice or
repositories of shared knowledge from trial-and-error learning outcomes (Nelson &
Winter, 1982; Winter, 2000). Understanding that the collective knowledge embedded in
social and organizational practices resides within practice-based and tacit experiences
enacted as collective action (Brown & Duguid, 2000), reflects the notion that “we can
8 The absence of the term “cognitive embeddedness” was discussed extensively during the review of the
social capital literature, however, as was in noted there, Zuckin and DiMaggio (1990) do offer a definition that is consistent with the intent of the term as used here.
71
know more than we can tell” (emphasis in original Polanyi, 1966: 4). The issue for
capability emergence, then, is one of understanding and absorption rather than just the
communication of declarative or procedural knowledge (Kogut & Zander, 1992, 1996;
Montealegre, 2002; Zollo & Winter, 2002). Here, the notion of absorptive capacity
within the group and by the individual is a particularly relevant contributor to the micro-
foundations of organizational capabilities that influence emergence (Cohen & Levinthal,
1990; Gavetti, 2005; Lorenzoni & Lipparini, 1999). Organizational knowing is not a static
embedded capability or stable disposition of actors, but rather an ongoing social
accomplishment, constituted and reconstituted as actors engage the world in practice
(Orlikowski, 2002). Because practice is not mindless and focuses on knowing rather than
knowledge, and agency within the structure of organization, cognitive embeddedness
reflects knowledge that is held by individuals, but is also expressed in regularities by
members who cooperate in a social network (Dyer & Hatch, 2006; Ethiraj et al., 2005;
Kogut & Zander, 1992). An individual’s ability to recognize novelty or deviation during
the performance of some function, to meaningfully communicate this insight to others,
where there is collective absorption of this insight among group members, is a critical
aspect of the contribution of social capital’s cognitive dimension to the building of
Brooks, 2005; Staw & Ross, 1978; Zollo & Winter, 2002). Experience gained in the early
stages of a capability’s lifecycle is highly informative for future performance: successful
performances preserve the patterns of structural, cognitive and relational
embeddedness which generated the performance, whereas early failures, in contrast,
reinforce the need for change and discount the patterns of social capital that resulted in
poorly fit performances. The future evolution of a capability, then, results from a
combination of both the emergence of social capital as well as the quality of capability
performance in prior periods. Once acquired, a capability’s evolution is set on a
trajectory whereby future learning and practicing required to advance development
85
may be much more dependent (Teece & Pisano, 1994; Teece et al., 1997; Winter, 2003;
Zollo & Winter, 2002) and focused on the refinement or exploitation of processes which
are known to result in legitimate success (March, 1991; Winter, 2000), marking a
transitional moment in the lifecycle of an organizational capability, from emergence to
development (Helfat & Peteraf, 2003). Social capital supports this trajectory; we argue
that social capital will vary in time with capability change, with rates of change mutually
co-evolving over time. To this end, we assert that:
H7: Social capital and capability performance will co-evolve over time such that
changes in rates of change in social capital will correlate to changes in rates of
change in capability performance.
While the emergence of social capital is argued to drive capability performance
within each time period, capability evolution and the co-evolution of the social capital—
capability performance relationship requires mutual adjustment, such that the stability
or variation in social resources and collective processes occur together over time.
Contributing to the literature by developing an understanding of how social networks
dynamically evolve around organizational capabilities and teasing apart the social
aspects of endogenous capability change are both important aims of this study, which
will address significant gaps in our understanding of the social micro-foundations of
capability performance and change.
86
Summary of Central and Peripheral Arguments
Building on the literary foundation developed in the previous chapter, this
chapter has emphasized the development and articulation of new organizational theory,
and the intended contributions which results from its exploration. To summarize, the
primary arguments asserted in this dissertation are that the emergence of social capital
has a significant influence on the performance of organizational capabilities, and that
the relationship between the emergence of social capital and the performance of
organizational capabilities is fundamental to capability evolution over time. In this
chapter the dissertation proposes that previous arguments regarding dependence based
on organization position, path, and process, articulated in the organizational capability
literature provide only a partial explanation of capability change. We have suggested
that organizational capabilities also evolve from variations in social capital developed
and deployed by network members. The interaction of structural, cognitive and
relational embeddedness is important because they influence the socially complex
micro-practices among group members which lie at the core of capability performance
and change.
Emphasizing an examination of the evolution of a single organizational
capability, threat identification, focusing on its performance and change over time helps
in part to overcome the tendencies in the capability literature to either fuse the
relationships between performance and outcomes together because they are hard to
87
distinguish or define; or to fail to recognize the importance of context in determining
the relevance of the performance-outcome relationship (Haas & Hansen, 2005: 19). This
research addresses both and lays out an agenda for a comprehensive study of two well
studied concepts: social capital and organizational capabilities. In what follows the
methodology and findings of this project will be discussed; these results examine each
of the relationships argued for in this chapter and provide insight into the relationship
between social capital and organizational capabilities from both cross-sectional and
longitudinal perspectives. Our findings provide answers to each of the four research
questions introduced earlier, and offer guidance in answering the question of whether
the emergence of social capital influences the evolution of organizational capabilities
more generally.
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Chapter Four: Research Design and Methodology
In the last chapter, a theoretical framework was developed to explain the
substance of social capital and organizational capabilities, as well as the pattern of
relationships between these constructs, concluding with a series of empirically testable
hypotheses to investigate both cross-sectional and longitudinal patterns of change. In
studying these relationships we propose to employ an experimental design, based on a
practice-based crisis simulation performed collectively in real-time. The simulation relies
on the Experimental Laboratory for Investigating Collaboration, Information-Sharing,
and Trust in organizations (ELICIT) simulation platform, using protocols consistent with
those used to study real-world organization members of Defense Research and
Development Canada - Toronto, Collaborative Performance and Learning Section.
Justifying this choice of research setting is not difficult in today’s turbulent times.
Moreover, the growing influence of research that Karl Weick and others (Weick, 1993;
Weick & Roberts, 1993; Weick & Sutcliffe, 2001) have done studying the impact of crisis,
threat, and disaster situations on collective sensemaking and collaborative performance
under extreme pressure, makes this context a highly relevant and an ever more valuable
one9.
9 Moreover, Leadership Quarterly recently (August, 2007) placed a call for research to explore “extreme
conditions” citing: “organizational scientists are beginning to call for research on “extreme” contexts rather than average situations, and panels and symposiums on dangerous contexts were conducted at the most recent Gallup Leadership Institute Summit, SIOP, and served as the central theme at the last biannual Global Leadership Conference at West Point. As noted by McKelvey (call for papers for 2008 Org Science Winter Conference), “managers don’t really need the advice of organization science scholars when faced with ‘average’ situations. It is when they confront extreme events, emergent outcomes,
89
This chapter offers a systematic approach to testing the hypotheses and
examines one specific research design which can viably focus on supporting or refuting
the core dimensions of the relationships among these constructs over time. The topics
discussed in this chapter address issues of research design and methodology, focusing
on issues central to the empirical examination of our theoretical model, including:
experimental design; sampling approach and sample characteristics; operational
definitions of dependent and independent variables; and construct measurement.
In this experimental simulation, the primary aim is to identify a collective threat
which requires active and ongoing coordinated collaboration among the simulation
participants, clearly illustrating the substance of an organizational capability. This
project explores the relationships between social capital and organizational capability
performance in real-time and under a variety of conditions. The aim is: first, to examine
whether and how social capital emerges during collaborative performance; second, to
isolate and examine whether and how social capital contributes to the performance of a
capability; and third, to determine the impact of social capital on the evolution of
organizational capabilities over time.
Sample Population, Characteristics, and Selection
For the purpose of effectively conducting this experiment, a convenience
sampling approach was selected because it was appropriate for early exploration of
irregularities, or crises that managers should find it useful to learn from organization scientists.” There is a need for study in this context, and an immediate applicability to management in all organizational types.
90
causal relationships (Singleton & Straits, 1999). The sample for this study consisted of
131 students enrolled in graduate (n = 120) and undergraduate (n = 11) studies at York
University. Demographic distribution relating to sample age, educational attainment,
gender and ethno-cultural diversity are presented in Tables 4.1 – 4.4, and provide
further elaboration of participant details. These characteristics are largely consistent
with hiring criteria for individuals currently working in those service roles most
commonly associated with emergency preparedness and crisis response in Canada (see
appendix A for a sample job description used in hiring), and provide some
representative similarity with requirements of real-world operators in this field. The
intent of the sampling design is to support data collection, which aims to investigate a
main causal effect between social capital and organizational capability performance.
Non-probability (non-random) convenience samples are often used in conjunction with
experimental designs based on the researcher’s desire to explore effects and discover
patterns among variables. Given limitations on time and resources, this sampling
method was not only appropriate for the needs of this project, but also consistent with
the selected experimental research design (Pedhazur & Schmelkin, 1991).
Our sample of 131 participants provided a reasonable sample size to allow data
analysis using a variety of means; first addressing socio-metric measures with UCINET
and later applying structural equation modeling and growth curve modeling techniques
(MacCallum, Browne, & Sugawara, 1996).
91
Table 4.1
Age Distribution of Sample
Variables N
Valid Missing Mean Median Mode
Indicate age in years: 125.00 6.00 29.65 28.00 27.00
Table 4.2
Educational Distribution of Sample
Indicate the level of your program of study: Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Undergraduate 11 8.4 8.7 8.7
Fulltime Masters 62 47.3 48.8 57.5
Parttime Masters 9 6.9 7.1 64.6
Doctoral 45 34.4 35.4 100.0
Total 127 96.9 100.0
Missing Non-response 4 3.1
Total 131 100.0
Table 4.3
Gender Distribution of Sample
Indicate gender: Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Male 38 29.0 29.9 29.9
Female 88 67.2 69.3 99.2
Alternate - please specify 1 .8 .8 100.0
Total 127 96.9 100.0
Missing Non-response 4 3.1
Total 131 100.0
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Experimental Design and Methodology
The explanation of the proposed experiment will be introduced in sections,
based on the linear sequential progression in which they would occur. As a result,
discussion will begin with preparation and recruitment, followed by the experiment
Table 4.4
Demographic Distribution of Sample
Indicate which of the following you
most self-identify as: Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Aboriginal (First Nations, Native
Canadian, North American Indian,
Metis or Inuit)
1 .8 .8 .8
Arab 3 2.3 2.4 3.2
Black 9 6.9 7.2 10.4
Chinese 19 14.5 15.2 25.6
Filipino 3 2.3 2.4 28.0
Korean 2 1.5 1.6 29.6
Latin American 5 3.8 4.0 33.6
South Asian (East Indian, Pakistani,
Punjabi, Sri Lankan, etc.) 10 7.6 8.0 41.6
South East Asian (Vietnamese,
Cambodian, Malaysian, Laotian, etc.) 1 .8 .8 42.4
West Asian (Iranian, Afghan, etc.) 6 4.6 4.8 47.2
White 46 35.1 36.8 84.0
Other - please specify 20 15.3 16.0 100.0
Total 125 95.4 100.0
Missing Non-response 6 4.6
Total 131 100.0
93
itself, concluding with the subject debriefing session. The general design of the
experiment proposed in this dissertation follows a ‘pre-experiment briefing
simulation one measurement simulation two measurement simulation three
measurement and debriefing’ approach (illustrated in Figure 4-1). The specific
aspects of the experimental design of the simulation have been included in the form of
an appendix (Appendix B), which was created by the simulation software developers as
a means of demonstrating the versatility and robustness of the system. The information
in this appendix provides the reader with a general overview of the underlying
experimental treatment or simulation in which the organization members will
participate, and illustrates the dynamics of player-simulation across all conditions. Here,
our interest is in using the platform as a means to test relationships of interest and as
such, we focus on the unique approaches and attributes specific to this research project,
rather than reiterating well-documented details of the simulation platform (outlined in
Appendix B; see also Ruddy, 2007).
Figure 4-1: Configuration of repeated measures experimental design
94
Unlike many social network studies, which rely exclusively on subjective self-
reports (such as name generators or information-quality recollection) in either a cross-
1991; Singleton & Straits, 1999; Stangor, 1998). In addition, by emphasizing the
128
importance of an appropriate sampling approach and focusing on the structure or script
of experiment, it is possible to create an immersive activity, thereby overcoming many
of the weaknesses stemming from artificiality discussed above. Recognizing the
underlying strengths of experimental methods in demonstrating causation, the method
and approach illustrated above includes a number of components intended to address
the most prominent threats to internal validity (Pedhazur & Schmelkin, 1991; Singleton
& Straits, 1999). Here, we addressed internal validity using approaches based in
research design and statistical methods, including those derived from: history (random
assignment), maturation and experimental mortality (multiple sessions conducted in a
single day), testing-effects and instrumentation (where data were derived from a
combination of objective and subjective measures), and subject awareness effects (well-
developed simulation scripts).
External Validity
External validity and the generalizability of results are typically considered
limited in a single incident (non-replicated) experiment, but can be enhanced by future
replication or cross-validation of the study and by varying the content of sample
composition (i.e. using probability sampling) (Pedhazur & Schmelkin, 1991; Singleton &
Straits, 1999; Stangor, 1998). To this end, provisions in this experiment have attempted
to address some of the limitations associated with threats to external validity. Decisions
with respect to reactions and interaction-effects due to testing sensitivity were
129
considered, thus avoiding priming effects of pre-test measures. In addition, we sampled
research participants whose age and educational background were relatively consistent
with real-world organizations in which the crisis simulation and underlying experimental
method were particularly relevant. Here, we randomized the participant identities using
pseudonyms and measured demographic differences to reduce potential confounding
effects that would encourage the interaction of selection biases with experimental
variables. Based on the choice of research platform, the selection of participants, and
the construction of the crisis simulation, the arrangement of this experiment was
intended to minimize the reactive effects of artificiality, thereby enhancing the external
validity of our findings to the best of our ability.
Concluding Research Design Remarks
In this chapter we outlined what we believe to be a systematic approach to
testing the relationships hypothesized in this dissertation, based on a research design
that would viably focus on modeling the core cross-sectional and longitudinal
relationships in our theoretical model. Our focus emphasized both the generalities and
the specifics of issues central to the empirical examination of our theoretical model,
including: experimental design; sampling approach and sample characteristics; and
operational definitions and measurement models of our variables. As noted earlier, in
this experimental design, we explored the relationships between social capital
emergence and organizational capability performance in real-time and under a variety
130
of simulated conditions, on the basis of a practice-based crisis simulation examined in
real-time. Given that the central research thrust of this dissertation was to unpack how
the emergence of social capital influences the evolution of organizational capabilities,
the study’s research design has provided what we believe to be an effective, relevant,
and viable platform for investigating the ascribed relationships among these constructs
both cross-sectionally and over time.
131
Chapter Five: Results and Findings of Study
Building on the results of our measurement modeling illustrated in chapter four,
this chapter contains a series of structural equation models which test our theoretical
arguments laid out in chapter three and illustrated in Figures 3-1, 3-2, and 3-3. More
specifically, we test the relationships of focal interest in this dissertation by investigating
how the emergence of social capital influences the evolution of organizational
capabilities. We begin by examining the patterns of relationships and model fit of three
cross-sectional structural equation models which reflect our repeated measures
research design. Although the factor structure of each model is identical across all three
measurement intervals, we evaluate each model independently without allowing any
temporal effects to judge comparative model fit among all three models. This cross-
sectional evaluation allows an investigation of the static relationships among structural,
cognitive, and relational embeddedness, social capital and capability performance at
three points in time.
Next, we take steps to evaluate the longitudinal effects of social capital on
capability performance and change. To do so we employ a growth curve modeling
approach developed to examine the correlation and covariance growth among latent
factors over time. This modeling technique makes possible the determination of rates of
growth for each of our two latent factors, social capital and capability performance, and
aids in determining whether these rates of change are correlated. Finally, we introduce
a longitudinal cross-lagged structural model that incorporates the results of all three
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rounds of our simulation, giving us the opportunity to examine the pattern of change
within the social capital – capability performance relationship taking into account cross-
sectional, latent growth, and cross-lagged effects in a single model. Only the results of
these analyses are presented in this chapter; for a review of the measurement models,
correlation tables or sample demographics, please refer to the details presented in the
previous chapter.
Cross-Sectional Model Fitting Results
Figure 5-110 illustrates the cross-sectional structural model reflecting the
conceptual arguments presented in chapter three. This single structural model is used to
investigate the structure of data collected in each round of the simulation, and provides
a standard of comparison across all three time periods to assess the overall pattern of
relationships among each of the first order and second order constructs as well as any
potential change in these patterns measured at distinct intervals. As noted in chapter
four, factor scores using maximum likelihood estimation have been calculated for
structural, cognitive and relational embeddedness based on item loadings and
reliabilities reported on earlier; these first order factors are now used in the estimation
of our structural model with social capital illustrated as a latent formative second order
factor. This formative construction requires a constraint on the social capital residual
error variance estimate (σ = 0.00) in order to fully identify our model. We undertook to
10
Structural models illustrated in this chapter omit item error terms and measurement residual terms for clarity and simplicity, although these have been included and accounted for in the modeling of each.
133
investigate the consequences of this constraint and provide results of a sensitivity
analysis in which the social capital residual error variance estimate was relaxed to a
more reasonable degree (σ = 0.45) and we reassessed model fit. We found no significant
change in model fit and little difference in the pattern of relationships among our
variables although the magnitude of the social capital – capability performance
relationship increased substantially (results reported separately in Appendix C). Based
on the conclusions of our sensitivity analysis, the results presented in this chapter will
be based on the more stringent standard (residual variance constrained, σ = 0.00) as it
ensures a consistent and conservative estimator in our cross-sectional modeling.
Assessments of the overall fit of our cross-sectional structural models were
established using several fit indices including chi-square test (χ2), goodness of fit indices
(GFI), confirmatory fit indices (CFI), and root mean square error of approximation
(RMSEA). These fit indices provide an estimation of the degree to which the data fit or
support our structural models in each of the measurement intervals; Table 5.1 presents
a comparative table of model fitting results in each period. For clarity, others have
suggested that the “chi-square test provides a measure of the inappropriateness of a
model if the model is not truly representative of the observed data” (Tsai & Ghoshal,
1998: 472), whereas GFI indicates the correspondence between observed and
hypothesized covariances, and CFI compares our proposed model to the null – saturated
and independence – models (Arbuckle, 2007).
134
Overall fit between the structural model and data captured in the first round of
the simulation suggested a strong correspondence (χ2 = 43.962, df = 38, p = .234; GFI =
.943; CFI = .986; RMSEA = .035 [p = .699]). These results indicate that our model reflects
a statistically significant approximation for the data as each of the indices represents a
better than acceptable model fit (Arbuckle, 2007). The regression weights for each
relationship illustrated in Figure 5-1 are provided in Table 5.2, as are the standardized
estimates and significance levels. Covariance and correlation estimates for the
relationships among structural, cognitive and relational embeddedness are outlined in
Tables 5.3 and 5.4. Factor score weights and the results of the standardized total effects
of each factor are contained in Tables 5.5 and 5.6 respectively; a summary of the model
fit indices associated with the data collected in round one are presented in Table 5.7 for
the reader to compare our results with those of the saturated and independence
models.
135
Figure 5-1: Structural Equation Model of Hypotheses with Comparative Cross-Sectional Relationships
t1: β = - .492 t2: β = - .554 t3: β = - .391
t1: β = - .246
t2: β = 1.555
t3: β = 2.118
t1: β = 1.136
t2: β = - .756
t3: β = - 1.619
t1: β = .462
t2: β = .354
t3: β = .289
t1: β = .163
t2: β = .903
t3: β = .981
t1: β = .617
t2: β = .746
t3: β = .658
t1: β = .229
t2: β = .145
t3: β = - .006
t1: β = .123
t2: β = .429
t3: β = .193
Capability
Performance
Capability
Accuracy
ID WHO
ID WHAT
ID WHERE
ID WHEN
Capability
Quality
A7A
A7B
A7C
Capability
Speed
1
1
1
Cognitive
Embeddedness
Structural
Embeddedness
Relational
Embeddedness
Social
Capital
1
136
Table 5.1
Comparative Structural Equation Model Fit Summary
Model χ2 df P χ2
/df GFI AGFI CFI RMSEA PCLOSE
Structural Model – Round One 43.962 38 .234 1.157 .943 .900 .986 .035 .699
Structural Model – Round Two 58.408 39 .024 1.498 .928 .878 .970 .062 .261
Structural Model – Round Three 38.391 40 .543 .960 .951 .920 1.000 .000 .909
Table 5.2
Regression Weights for Structural Model (Measurement Interval One)
Estimate Standardized Estimate S.E. C.R. P
Social Capital <--- Structural Embeddedness -.300 -.492 .147 -2.040 .041
Social Capital <--- Cognitive Embeddedness -.246 -.392 .157 -1.563 .118
Social Capital <--- Relational Embeddedness .786 1.136 .166 4.719 ***
Capability Performance <--- Social Capital 1.000 .462
Model One – Constrained Cross-sectional Parameters in t1 and t2
3.582 6 .733 .597 .991 1.000 .000 .853
Model Two – Constrained Autoregressive Parameters for Social Capital in t1
2, t1
3, t2
3
10.196 7 .178 1.457 .977 .986 .059 .362
Model Three – Constrained Autoregressive Parameters for Capability Performance in t1
2
and t2
3 3.635 6 .726 .606 .991 1.000 .000 .848
Model Four – Constrained Cross-lagged parameters for Social Capital to Capability Performance in t1
2 and t2
3
4.932 6 .553 .822 .987 1.000 .000 .724
Model Five – Fully Constrained Model in all Intervals
95.656 13 .000 7.358 .791 .629 .221 .000
* In this instance constraining parameters refers to the imposing two or more paths to estimate freely but as equivalent to each other (i.e. identical relationships)
166
The test of covariance among the slopes of factors in our latent growth curve
modeling failed to provide support for our coevolution hypothesis, and in the strict
sense of coevolution this is an accurate conclusion to draw from our findings. However,
the results of our cross-lagged regression modeling do suggest that more than cross-
sectional effects are at play in the relationship between social capital and capability
performance; the presence of longitudinal cross-lagged and autoregressive effects also
contribute to future performance and change. For social capital, each autoregressive
path presents highly significant growth across measurement intervals (Social Capital
(t1
2) β = .658, p < .001; Social Capital (t2
3) β = .582, p < .001; Social Capital (t1
3) β =
.352, p < .001) suggesting the presence of emergence and a trajectory of growth
although at diminishing rates. The autoregressive relationships of capability
performance are also following a similar path (Capability Performance (t1
2) β = .422, p
< .001; Capability Performance (t1
2) β = .277, p < .001). Taken together, the evidence
we have provided of cross-sectional, longitudinal growth and cross-lagged effects of the
social capital-capability performance relationship provide a compelling case in support
of co-evolutionary change. In practice we have two distinct constructs changing
significantly in relation to each other over time, which at least minimally meets the spirit
of coevolution, however, based on our findings we are tempted to concede that our
results do not strictly meet the definition of coevolution as laid out in the seventh
hypothesis. We return to this point in depth in our discussion of this research project.
167
Summary of Research Findings
In this chapter we have applied three distinct modeling techniques to determine
whether support could be established for each of our hypotheses relating the
relationship between social capital and capability performance over time. In general,
our results support the idea that the emergence of social capital is influential in
generating capability performance, although not monotonically so as our individual
results reveal. In addition our findings demonstrate that social capital and organizational
capability performance are growing and evolving over time as revealed in the modeling
of latent growth and cross-lagged effects. In the following chapter, we discuss the
implications of our findings for theory and practice, and consider what these findings
mean for scholars in the field currently examining social capital, organizational
capabilities, and the relationship between the two.
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Chapter Six: Research Contribution, Discussion, and Implications
This study began with a question: how does the emergence of social capital
influence the evolution of organizational capabilities? Focusing on the relationships
among structural, cognitive and relational embeddedness, and how these influence the
growth of social capital from the earliest phases of emergence, we have shown how
social capital influences organizational capability performance. Our findings support the
proposition that social resources are influential in generating and sustaining
coordinated collective performance. These findings suggest that the three dimensions of
embeddedness do not arise and enhance social capital monotonically, instead they are
highly interrelated and interdependent, which suggests that building social capital is a
fitful process relying on combinations of interpersonal connection, awareness and
agreement which may over time develop into social cohesion, collective mindsets and
deep trust. Social capital consistently demonstrated its potential to contribute to
capability performance, increasing the rate at which capability performance occurred as
well as the quality of performance over time. The emergence of social capital it seems
does meaningfully enhance collaborative performance, both in the present and in the
future.
Capabilities can evolve quickly over time, and social capital does have a role in
shaping this change. Our analyses also illustrate the power of endogenous change in
each subsequent period of investigation and provides evidence of the capacity for
capabilities to change themselves (Helfat & Peteraf, 2003). Experience no doubt
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accumulates with each consecutive attempt to identify the source of an impending
threat (Zollo & Winter, 2002), yet the significant role of social capital builds over time as
embeddedness increasingly facilitates the sharing of knowledge and experience. Our
results bear this out, demonstrating both the cross-sectional and longitudinal impact of
social capital on capability performance and change. In sum our findings illustrate how
social capital and capability performance dynamically emerge and evolve from their first
instantiation. This final point, that social capital appears to be a persuasive determinant
in the lifecycle of organizational capabilities, begins to consider each dimension of social
capital – structural connections, cognitive contribution, and relational linkages – in
terms of its ability to contribute unique yet complementary utility during the process of
capability building and change. The relationship between the emergence of social
capital and the evolution of organizational capabilities, and its impact on longer term
capability change, warrants further investigation.
Winter and Zollo suggest that “*t+he literature does not contain any attempt at a
straightforward answer to the question of how routines – much less dynamic
capabilities – are generated and evolve” (2002: 341). Others have credited strategic
interventions with driving capability change (Teece et al., 1997): episodic interventions
punctuate operating routines allowing for the reconfiguration of capability micro-
foundations and bringing about improved fitness (Helfat et al., 2007). Endogenous
change and capability evolution have only recently received due consideration (Helfat &
Peteraf, 2003), propelled by a search for the constituent parts of organizational
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capabilities – the micro-foundations and micro-processes that compose the content of
dissertation is among the first that we are aware of to examine the emergence and
evolution of capability performance in a single study, and to empirically investigate
social micro-foundational sources of endogenous capability change. The presumption
that a capability hasn’t occurred until reliable performance has been established has
posed an obstacle to the study of capability emergence (Helfat & Peteraf, 2003: 999),
because it has limited the exploration of capabilities to periods of ‘reliable’
performance. This study however takes us to the performance period just preceding
‘reliability’, where ad hoc performances are evolving toward convergence and reliability.
The experimental methodology employed in this research captures the ‘co-emergence’
of social capital and capability performance with our first interval measurements, and
illustrates ‘co-evolution’ with each consecutive interval, as the two constructs
dynamically change over time.
How do social networks emerge and grow? And how does their growth impact
capability performance? This research examines these two issues, focusing on the
emergence, growth, and dynamic change of social capital and organizational capabilities
among individuals working collectively in real time. Social capital emerges and grows
from repeated interpersonal interactions within networks of practice; based on a
growing history of successful interactions, cognitive convergence and relational
closeness grow among network members. For organizational capabilities, social
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resources are explicated as both a constituent and catalyst of capability change: guiding
and supporting effortful collaboration as capabilities first unfold; later responsive to
subsequent revision, refinement, and reification which systematically embeds network
architectures into collective memory. Social capital significantly enhances capability
performance by improving the quality of performance and speeding the pace at which
performance occurs. Our research reveals that social capital constituted of structural,
cognitive, and relational embeddedness is a significant micro-foundation of capability
performance and change. The dominant “conceptual analyses of the process by which
capabilities change over time have often relied on the idea that dynamic capabilities
must act upon other (operational) capabilities in order to change them” (Helfat &
Peteraf, 2003: 1004), and only recently have we begun to challenge this dominant
perspective with endogenously dynamized views of capability change.
Examining the evolution of a single organizational capability, threat
identification, and focusing on its performance and change over time, helps in part to
overcome the tendencies in the capability literature to either fuse the relationships
between performance and outcomes together because they are hard to distinguish or
define, or else to fail to recognize the importance of context in determining the
relevance of the performance-outcome relationship (Haas & Hansen, 2005: 19). In this
study we have not only done both, we have laid out an agenda for a comprehensive
study of two well studied concepts: social capital and organizational capabilities.
Applying a new methodology, the findings of this project have generated new insight
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into the relationship between social capital and organizational capabilities from both a
cross-sectional and a longitudinal perspective. Our findings provide answers and offer
guidance in answering questions about how the emergence of social capital influences
the evolution of organizational capabilities more generally.
While researchers and managers continue to wrestle with the twin issues of
network emergence and endogenous capability change11, in this project we have
investigated the origins, mechanisms, and implications of social capital emergence on
future patterns of performance. We have also investigated whether and how emerging
social resources imprint organizational capability trajectories during their co-emergence.
Our capacity to investigate the emergence and evolution of these constructs is largely
due to the unique experimental methodology that we have applied in this research.
Neither the social capital nor the organizational capability literatures have a tradition of
employing experimental methodologies; they have instead relied upon a variety of
other qualitative and quantitative approaches to examine their subject matter. As a
consequence for the field, many questions about how these constructs emerge and
evolve – independently or jointly – have remained unasked and unanswered. In broad
strokes, this study begins to unravel the relationship between social resources and
collective processes by arguing that capabilities can and do endogenously emerge and
evolve with social capital. The emergence of social capital provides organizational
11
For example, consider Organization Science’s two recent calls for additional attention to these topics: Ahuja and colleagues (eds.) special issue “The Genesis and Dynamics of Networks”; and, Lewin & Burton’s (co-chairs) call to focus on co-evolutionary and endogenous capability change in the upcoming OSWC-XI.
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capabilities with much needed social infrastructure, but also embeds patterns of
network dependence into the capability, preconditioning the capability’s future
trajectory by systematically supporting its future growth and stability.
Can capabilities change themselves, and if so how? Some indicate that we should
look to the situated social context for cues (Collis, 1994; Haas & Hansen, 2005), and that
social resources present in capability founding systematically pattern future processes
“by preconditioning the emergence of a capability” (Helfat & Peteraf, 2003: 1001). Until
now, this proposition has remained a largely untested assumption, receiving tacit
endorsement based primarily on retrospective accounts (Gulati, 1999; McEvily &
Marcus, 2005; Reagans & Zuckerman, 2001). The social complexity that underpins
collective processes results from combinations of uniquely experienced individuals
collaborating individually and in concert, which at founding provides an “initial source of
heterogeneity among capabilities” (Helfat & Peteraf, 2003: 1001). The social capital
developed during the early phases of capability development subsequently patterns
future legacies (as memories, truces, or aspirations, for example, Nelson & Winter,
1982), further preconditioning capability performance trajectories as our results
suggest. But our findings also support the role of performance feedback, or more
accurately feed-forward, in generating an endogenous impact on capability change.
The feed-forward effects of the past, both autoregressive and cross-lagged,
shape the evolution and co-evolution of social capital and capability performance. Both
are changing over time, and the pattern of relations resulting from our modeling
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reinforces the social complexity hypothesized by others (Collis, 1994; Eisenhardt &
Martin, 2000). Our findings suggest that co-evolution between the constructs is more
complex than expected; the rates of social capital and capability performance growth
are not equal over time, nor is either occurring in a linear path as our modeling
illustrates. Only when we include both the individual growth curve effects and the cross-
lagged effects simultaneously do we begin to get a clearer sense of the foreshadowing
of social capital on capability performance. This suggests that the co-evolution of social
capital and organizational capabilities relies upon mutual adjustment, such that the
stability or variation of network and processes occur together over time in response to
capability fitness.
Contributions to the Organizational Capabilities Literature
This study is one of only a few to empirically examine the role of social resources
in the development and change of organizational capabilities, and among the first to
investigate the impact of social micro-foundations on capability performance.
Unpacking the ‘black box’ of capability building, performance and change is an often
called for but seldom accomplished pursuit (Abell et al., 2008; Felin & Foss, 2005, 2006;
Helfat & Peteraf, 2003). Our study brings the individual to the foreground of capability
performance, highlighting the importance of social capital in creating positive
performance in the present and shaping patterns of performance in the future. These
findings demonstrate the significance of embracing a socialized perspective in the study
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of capability performance, as well as the consequences of omitting social micro-
foundations from future studies of capability change. Opening the ‘black box’ of
capability change is an important first step in expanding our knowledge of the dynamics
of organizational adaptation and evolution. Unlike previous research which has focused
on post hoc examinations of capabilities (for example, Montealegre, 2002; Tripsas &
Gavetti, 2000), this work examined the preliminary stages of capability development in
real time to shed new light on how capabilities first emerge. Management theory and
application can certainly be enhanced by examining the micro-foundations of capability
change (Abell et al., 2008; Teece, 2007). Studying patterns of social capital emergence
offers a unique contribution to the understanding of how capabilities evolve because it
begins to untangle the causal factors that drive capability change from a socialized
perspective rather than an historical one based on the study of positions, paths, and
processes. Proponents in the social capital literature have asserted the concept’s
importance in generating performance outcomes, but until now little about whether the
causality of these arguments was appropriate or how the patterns of influence occurred
was known.
A pressing question in the resource-based theory literature revolves around the
origins of organizational capabilities, as Zollo and Winter (2002: 341) outline: “*t+o our
knowledge at least, the literature does not contain any attempt at a straightforward
answer to the question of how routines – much less dynamic capabilities – are
generated and evolve.” We do not claim to resolve the question fully, but we do add
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two missing pieces to the answer. First, the intent of this research project was to
explicitly examine how capabilities develop and evolve over time beginning with the first
collective attempts at performance. As a result, our data capture both the initial
collective efforts to generate performance as well as the changing trajectory of
performance over time, and provide a picture of this process. Our results illustrate the
path of progress along which capability performance evolved, and demonstrate the role
of individuals in affecting the capability micro-foundations that make this happen.
Others have highlighted the “need to explain the individual-level origins, or micro-
foundations of collective structures as they arise from individual action and interaction,
while extant work seems to take organization, and structure more generally for
granted” (Felin & Foss, 2006: 255); a contribution of this project is that it actually
investigates and explains (rather than simply declaring the need to explain) the origins
of an individual-level micro-foundation of capability performance, and demonstrates its
impact on capability change over time.
A second contribution to our understanding of the origins and evolution of
organizational capabilities lies in the treatment of capability performance as inherently
social. While links between organizational capabilities and other facets of organization
are gaining prominence in the resource-based view literature, we still know very little
about the social constitution of capabilities, let alone how social aspects impact
capability emergence or change over time. This dissertation demonstrates that the
social context of work matters in its ability to shape collaborative practice, and we have
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generated a better understanding of the social network-collective process relationship.
Our results illustrate that the capacity to build a new capability is contingent on the
socially complex coordination of routines, resources and people, and that social capital
is central to effectively coordinating performance. In our case social capital infuses
capabilities with access to varied and diverse sources of information, the capacity to
absorb and integrate information within the network of practice, and relational
connections that foster trust and trustworthiness among organization members. These
social resources shape the performance of our organizational capability ‘threat
identification’ directly, and impact the trajectory of its performance over time as well.
Successful performance in our context requires that network members communicate,
share information and maintain a shared situational awareness through a process of
collaboration and functional cooperation; social capital serves as the infrastructure
through which these social resources flow. These results suggest that the interactive
context of capability development may be an important element in explaining
capabilities and their effectiveness as dynamic entities.
The issue of capability change remains somewhat contested in the literature (for
examples of varying perspectives refer to, Eisenhardt & Martin, 2000; Teece et al., 1997;
Winter, 2003), however Helfat and Peteraf (2003: 1004) remind us “that capability
building and change do not require dynamic capabilities”, the capacity to change resides
within capabilities themselves. Capabilities have the capacity to change themselves by
altering the composition and organization of their micro-foundational parts. This
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dissertation gives credence to prior claims of endogenous capability change by
demonstrating how practice-based and process-based learning longitudinally impact
performance (Helfat & Peteraf, 2003; Zollo & Winter, 2002). By teasing apart the social
aspects of endogenous capability change and illuminating an important social micro-
foundation of organizational capabilities, this study has advanced our thinking about
how emergence and evolution occur. While previous managerial intervention strategies
have focused on the advantages of the capacity to rapidly update organizational
processes, we caution that an unintended consequence of such updating may be to
disrupt existing social capital networks. Rather than treating social aspects of capability
performance and change as an exogenous accessory, our findings illustrate that social
resources provide a significant contribution to the emergence and evolution of
organizational capabilities. Social capital and social networks more broadly warrant
greater inclusion in the study of capability micro-foundations as they have been shown
to provide the social infrastructure that stabilizes the variability of performance while
allowing progressive evolution over time.
Contributions to the Social Capital Literature
This study has incorporated a relatively rare approach to the study of social
capital, as we are aware of no other published investigations of longitudinal
experimental simulations exploring the emergence of social capital, or the inclusion of
real-time whole-network data collection. As noted earlier, little empirical work has been
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done to examine how social capital emerges and evolves within an organizational
context. While previous work has suggested that many forms of social capital have
developed through a history of repeated interaction, through mutual dependence and
reliance, and through social similarities that differentiate one group from another
and coordination (Branzei & Fredette, 2008; Levinthal & Rerup, 2006), and collaborative
interrelating (Weick & Roberts, 1993) to function effectively. The effects of social capital
in contrasting social contexts may vary significantly based on the nature of the
capability. Contrasting how social capital facilitates the use of an existing stock of
capabilities versus the acquisition of new capabilities would provide valuable insight to
the research community. Understanding the conditions under which existing stocks of
social capital help or hinder the performance of new and established capabilities would
assist organizations struggling to keep pace with changing environmental demands.
The methodological approach employed in this research has allowed us to
examine longitudinal growth between social capital and capability emergence across a
series of measurement intervals. We believe that taking a systematic approach to
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testing the relationships hypothesized in this dissertation, one based on a research
design that viably focused on modeling both the core cross-sectional and longitudinal
relationships in our theoretical model, offers new insights into the dynamics of
capability development. Our protocols were consistent with those used to study real-
world organization members of Defense Research and Development Canada - Toronto,
Collaborative Performance and Learning Section. Given that the central research thrust
of this dissertation was to unpack how the emergence of social capital influences the
evolution of organizational capabilities, the study’s research design has provided what
we believe to be an effective, relevant, and viable platform for investigating how social
relations affect the emergence of capabilities.
The explicit consideration of social capital in the process of capability evolution
provides a unique, yet essential, glimpse into the socio-relational core of capability
change because it recognizes the novel and idiosyncratic resource value of social capital
(Adler & Kwon, 2002; Burt, 2000; Moran, 2005). While each of these fields – social
capital and organizational capabilities – warrant independent study in their own right,
investigated in tandem they present the opportunity to make a significant contribution
to our understanding of organizational performance. Their study has allowed us to not
only describe the process of how emergence occurs, but also to explain what triggers
evolution and why change occurs – each fundamental in making a contribution to
organization and management theory.
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Chapter Seven: Research Conclusions
Our investigation of social capital and organizational capabilities in combination
significantly contributes to our understanding of organizational performance and
change. This study has allowed us to demonstrate how the process of social capital
emergence occurs, and to explain how it relates to the triggering of capability evolution.
As a result, this research project has generated greater insight into how organizational
capabilities grow and evolve, and how social capital contributes to these processes. By
better understanding the role that social capital networks play in the emergence and
evolution of organizational capabilities, we open the door to a variety of intervention
strategies amenable to the specific context in which the organization finds itself. Adding
some measure of control and predictability to capability evolution is important because
it may allow organizations to take action to encourage, stabilize, or discourage capability
change via specific intervention mechanisms, and provide an opportunity to maintain
alignment between internal processes and performance objectives.
The aim of this dissertation was to contribute insight to the management
literature by examining the micro-foundations of organizational capability emergence;
demonstrating that the social, relational, and structural context of work matters,
especially in its ability to shape collaborative practice and contribute to the collective
ability to meet organizational needs. Focusing on capability change offers a unique
contribution to the understanding of organizational capabilities because it begins to
question the causal factors underlying the origins and emergence of organizational
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capabilities beyond the study of positions, paths, and process evolution (Dierickx & Cool,
1989; Nelson & Winter, 1982; Teece et al., 1997). Our attempt at opening the ‘black box’
of capability emergence is an important first step in expanding our knowledge of
dynamics of organizational adaptation and evolution; understanding how the social
micro-foundations of organizational capabilities function is a necessary antecedent to
further enquiry in the line of study (Felin & Foss, 2005). This study has reduced some of
the ambiguity surrounding the valence of social capital in collective performance. While
proponents in the social capital literature have asserted the concept’s importance in
individual performance outcomes such as advice-seeking (Cross & Sproull, 2004), we
know very little about whether these arguments are appropriable to collective settings
or how differing configurations of social capital influence collaborative performance.
The results of our study provide some insight in this regard. Advancing our collective
thinking about organizational capabilities will require further investigation of the
remaining gaps in our understanding of capability micro-foundations – of which there
are many. By determining not only whether social capital is important, but how it is
important in the building and evolution of organizational capabilities this dissertation
has made strides in this effort. This dissertation has proposed that previous arguments
regarding dependence based on organization position, path, and process, articulated in
the organizational capability literature provide only a partial explanation of capability
change. We have suggested that organizational capabilities also evolve from variations
in social capital developed and deployed by network members.
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The interaction of structural, cognitive and relational embeddedness is
important because it influences the socially complex micro-practices among group
members that lie at the core of capability performance and change, shaping the social
micro-foundations of organizational capability evolution. Linking these distinct fields of
thought in a longitudinal framework illustrating their combined performance is a
significant contribution in its own right. However, connecting the performance
implications resulting from mutual emergence and co-evolution of social capital and
organizational capabilities constitutes a potentially important step forward. Therefore,
understanding how social capital emerges and organizational capabilities evolve is a
worthwhile endeavor at this time, as it offers organization scientists and managers the
opportunity to take action in a deliberate, purposeful, and timely fashion to encourage
capability change and enhance organizational performance.
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APPENDIX A: Threat Management Analyst Job Description Reference Number: 08-CSIS-07-028 Closing Date: 2009-12-31 Job Summary The Canadian Security Intelligence Service (CSIS) is seeking motivated and responsible individuals to serve as Analysts for the Threat Management Centre (TMC). Candidates must possess excellent analytical and research skills, excellent interpersonal and communication skills as well as possess the ability to work under pressure reliably and autonomously within the TMC team. Candidates must also possess good knowledge of current affairs, of international geography as well as of national and international media (print, broadcast, electronic, Internet). The TMC operates on a 24 hours a day, 7 days a week basis. Analysts are required to work shifts and could at times be expected to work alone on shifts. The functions may involve the following:
ensure a continuous and reliable alert service and point of contact to CSIS for employees and others;
coordinate effective review and analysis of various information and to coordinate an effective response pertinent to a special event and/or incident for CSIS;
offer a high quality service to CSIS employees, to our partners in the intelligence community as well as to the public in both official languages.
Education Undergraduate degree and two (2) years related experience or a three (3) year Community College Diploma and three (3) years related experience. Any higher level of education could be recognized as related experience. Experience Candidates must possess a minimum of two (2) years experience in research and analysis, possess a minimum of two (2) years experience in writing reports and/or briefs and must also possess experience in providing service to the public. A written test will be administered. Only the top ranking candidates will be considered.
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Who Can Apply: Canadian citizens residing in Canada for the last ten (10)
consecutive years. Security Requirements Candidates must have no criminal record, be drug free for the last twelve (12) months and be able to obtain a Top Secret security clearance. This process involves a security interview, a background investigation that includes credit and financial verifications as well as a polygraph examination. Language Requirements: Bilingual imperative (C/B/C) Salary Range: $59,540 to $72,460 per year. Salary is commensurate with
qualifications/experience. Location: CSIS National Headquarters, Ottawa, Ontario
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APPENDIX B: ELICIT Description12
Background: In “Power to the Edge”, Alberts and Hayes (2003) argue that missions designed with superior shared awareness, trust and self-synchronization will perform with greater speed, precision, effectiveness, and agility than missions conducted under traditional hierarchical command structures. They further argue that this is achieved by placing decision rights at the “edge of the organization,” close to the points of consequence. As part of its network-centric warfare initiative, the Command and Control Research Program (CCRP) is engaged in developing and testing principles of organization that significantly revise traditional command and control practices, transferring power and decision rights to the edge of the organization. In order to test these assertions, CCRP needs to frame testable hypotheses about the relative effectiveness of edge organizations in comparison to other methods of organization through a series of real-world experiments. In order for CCRP to undertake such experiments, the following capabilities are needed: Replicable and valid measures of shared awareness, self-synchrony and trust.
Ideally, such metrics need to be derived from observed behaviors in organizational settings.
Non-intrusive instrumentation that can be used to capture real-time behavioral
metrics about different types of organizational interactions. Automated tools and techniques that can accommodate testing for the different
factors that might affect “edge performance” with respect to shared awareness, trust, and self-synchrony.
Privacy controls and methods of apparatus deployment and administration that do
not themselves entail significant organizational changes or overhead. Another major requirement for conducting such experiments is that they compare the relative effectiveness of edge organization to traditional command and control
12
Appendix B contains an abridged version of the complete experimental design overview offered in Ruddy (2007), which is consistent with the documentation found elsewhere Parity Communications, 2006).
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principles in missions that either mimic real world missions or are themselves actual missions. By creating and evolving the ELICIT software platform, tools and procedures, and by conducting ELICIT experiments we seek to test the validity of these propositions in a controlled environment and within a controlled task domain. The objective of the experiment design is to conduct a series of online experiments to compare the relative efficiency and effectiveness of traditional command and control (C2) vs. self-organizing, peer-based edge (E) organizational forms in performing tasks that require decision making and collaboration. Meeting the Core Requirements: The major efforts in this project included the design, development and testing of the software platform on which to run the experiments; the design and execution of the experiment task (including supporting materials); and data analysis. This project addressed the following specific objectives: Develop system-based behavioral measures of “shared awareness.” By controlling
for the distribution of content and its visibility, and capturing in time logs when different subjects have shared awareness, the project was designed to compare shared awareness among subjects and its impact upon the successful completion of a mission.
Develop system-based behavioral measures of “trust” by monitoring subject
interactions in terms of reciprocity, responsiveness, number of interactions, and willingness to share content. Such trust measures can be used as predictors of mission effectiveness and timeliness.
Develop subject-based indicators of “self-synchronization” based upon the
effectiveness of trust and shared awareness in reducing decision cycles. Approach: The ELICIT software was developed and iteratively refined using live subjects. The experiments are controlled-hypothesis testing experiments. The experiment task is to identify the who, what, where and when of an adversary attack based on simple information facts (called “factoids”) that become known to a team. The independent variable is whether a team is organized using traditional command and control hierarchy or using edge organization principles.
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Experiment Software Platform: The ELICIT software is a downloadable software application that is installed on each subject’s laptop. It was built on top of the open source Higgins Trust Framework software developed as part of the SocialPhysics project affiliated with the Berkman Center for Internet and Society at Harvard Law School. The software allows CCRP and other experimenters to precisely model specific C2 processes, as well as edge organization processes, and to fully instrument all interactions. The ELICIT software platform includes a measurement capability built over a messaging infrastructure. Unlike existing software messaging and analysis technology, this open source software was uniquely designed to enable shared awareness, trust building and self-synchronization. The ELICIT platform was designed to be configurable to support both initial and follow-on experiments. The software, which is built on the Eclipse Rich Client Platform (RCP), offers modular, plug-in based design. Thus it is relatively easy to modify the software to support different experiment features or to add further communications mechanisms to determine their impact on team efficiency. Experiment Design – Purpose: The objective is to conduct a series of online experiments to compare the relative efficiency and effectiveness of command and control (C2) organizational structure with a networked, peer-based edge (E) organization in performing tasks that require decision making and collaboration. One of the key propositions of edge organization is that unknown parties, when given a shared awareness, will collaborate and self-synchronize their behaviors to achieve common goals. It is also argued that by placing decision rights at the “edge of the organization,” close to the points of conflict and consequence, more efficient and effective decisions can be made than when decision rights are concentrated and controlled through a hierarchical command and control structure. (Alberts and Hayes, 2003) The experiment challenge is to provide an online test bed where the efficiency and efficacy of command and control and edge organizational models can be compared for tasks that mimic real world conditions and challenges. By isolating several of the key structural and interactive factors that characterize command and control and edge organizations, a series of experiments and measures can be constructed to compare their relative effectiveness and efficiencies for an identical set of tasks.
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The controlled hypothesis testing experiments were designed to further understanding of the advantages of edge organization that are being conducted as part of much larger efforts in investigating the applicability of edge organization. Approach: The approach taken was to design an online multi-subject task that is sufficiently rich that it mimics issues in real-world conditions. At the same time it needed to be simple enough to make it possible to control for multiple structural and interactive parameters that differentiate between command and control-based and edge-based organizational models. The experiment challenge was to construct an experiment task that had the following characteristics: Highly relevant to real-world situations Of current interest to the DoD community Of interest and engaging to experiment subjects Multi-user, with each subject treated equivalently Abstract enough that it can be fully modeled Capable of being constructed in several versions (to support practice round and
multiple rounds of experiments with the same subject group.) Short enough so that both the practice round and actual round can be conducted in
a reasonable amount of time Difficult enough that it is not trivial to accomplish regardless of the organization
structure used Comprehensive in its range of difficulties, so that the effects of organizational
structure can be seen Flexible, so it can be adapted to new settings by changing names, tables, etc.
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By developing the ELICIT software platform, we were able to precisely model specific C2 and edge organization processes, and instrument all interactions. By abstracting complex tasks to simple interactions we were able to control for variations in subject capability and skill, and for the inherent variability in live situations that have confounded the data in other experiments. This approach allows the experiments to focus on fundamental issues of organizational design and to isolate factors that can be used to improve efficiency and effectiveness. The modular software can be modified to test additional approaches in future experiments. In the experiment, subjects are randomly assigned to two groups: “Edge” (E) and “Command and Control” (C2). Each group is to identify the who, what, where and when of an adversary attack by combining and sharing a set of information factoids that are distributed among the subjects. There are four kinds of factoids corresponding to the four kinds of information required (who, what, where and when). Like pieces of a puzzle, each contains a piece of information, but each alone is insufficient. In the experiments conducted to date, all factoids were factually correct; no incorrect information was used. Since subjects have only partial information, they must collaborate and exchange information with other subjects in their group in order to complete the task. All interactions between subjects occur through a software application resident on each subject’s computer. In either group, any subject can communicate with any other subject, although all communication occurs only as mediated by the software application. The experiment software monitors the progress of the information gathering task and declares the trial over when each individual has identified the who, what, where and when – or when the experiment times out. The group of subjects (E or C2) that completes the task first is declared the “winner.” In order to minimize any side effects from variations in previous knowledge of subject matter or the ability to absorb subject information, the information in the task is highly abstracted. The experiment is fully instrumented by the ELICIT software. It records the time and particulars of every action by each subject. Organization of the C2 Community: In the C2 organization, there are four teams of four members each plus an overall cross-team coordinator (designated in the chart as E5). The four teams are organized along
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the lines of a traditional hierarchical command structure, each with a leader. The following shows the hierarchical relationship between the overall coordinator (E5), the four leaders (A4, B4, C4 and D4) and their subordinates: Team A is from country A. Teams B, C and D are from countries B, C and D respectively. The four teams (A, B, C and D) each have a functional specialization: Team A is focused on who, team B on what, team C on where, and team D on when. The overall coordinator coordinates information among the team leaders across team boundaries. Organization of the E Community: In the E community the subjects are organized along edge principles. Unlike the C2 organization, there is no hierarchical decomposition nor is there specialization by functional area. Decision rights are decentralized: subjects decide for themselves what aspect of the task to work on, and in some situations they can choose other subjects to work with. Control is achieved entirely through the shared awareness provided by
universal access to information on shared information systems. NOTE: The above diagram is an organization chart; it is not a description of the possible communication flows. For example, subjects are able to share information to any other subject, not just along the lines shown above. Details of Experiment Design: This section provides additional details of the experiment design. Subjects:
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Subjects are randomly assigned to two 17-member groups, C2 and E. The subjects are asked to perform the task using a software application that has been pre-loaded onto their computers. All experiment communications occur between anonymous identities, so previous relationships between subjects are irrelevant. The subjects need not be physically in the same location, as all of their interactions are mediated through the software application. Subjects see and use a simple screen that contains: A message queue (looks like an email inbox) that displays messages from the
moderator as well as factoids (which look like one-line email messages) A multi-tabbed information display area that displays information about other
organizational members as well as simplified Web site-like lists to which subjects can post factoids they have received
A set of actions (menu items) the subject can take. The important actions are: (i)
Sharing a factoid with another subject; (ii) Posting a factoid to one of the Web site-like lists; (iii) Pulling to see what is on a Web site-like list; and (iv) Identifying one or more aspects of the adversary attack (when the subject thinks they know some or all of this information).
By tightly constraining the forms of communication, the experiment controls for variations in communications styles among the subjects. Task Objective: The subjects are given the objective to solve the puzzle of the location, time, target and group responsible for the adversary attack. Instructions are tailored to fit either the E organization (designated the “A” group) and its roles or the C2 organization (designated the “B” group). All subjects are instructed that they are free to work on any aspect of the task. Subject Roles: The experiment software automatically provides a URL with group-specific instructions to each subject at the start of an experiment trial set. Factoids:
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During each round of the experiment, the application delivers four “factoids” to the inbox of each subject. Group members use these factoids to help identify the adversary attack. Two factoids arrive at the beginning of the experiment round. An additional factoid is distributed five minutes later and one last factoid five minutes after that. All of the information necessary to identify the adversary attack has been distributed to the subject group within the first 10 minutes after the start of an experiment round. There are four types of factoids that represent information about the anticipated attack: Who factoids – the likely actors What factoids – the target Where factoids – the country When factoids – the month, day and time. Initial Factoid Distribution: There are 68 factoids, including 4 expertise factoids. To model a hierarchy (C2) organization, in which team leaders traditionally have more expertise than their team members, each of the four team leaders is given an “expertise” factoid that represents pre-attained knowledge. In the E case, these expertise factoids are disbursed within the community at random. Some of the 68 factoids are more important than others. The more important ones are considered key factoids. Expertise factoids are special key factoids. The remaining non-key factoids are distributed among the subjects so as to ensure that no subject receives more than 1 key factoid. The base factoid sets are available at http://www.dodccrp.org/html3/elicit.html. This phased factoid distribution is designed so that the task can’t be solved until the last distribution is made. Distribution of factoids is controlled and specified in factoid set tables. Four complete factoid sets where created. Factoid set 4 is the easiest. Factoids sets 2 and 3 are very similar. For the initial experiments, all live subject tests were performed using factoid set 4-17 for the practice round and 1-17 for the actual round.
In subsequent trials, factoid sets and or players can be changed. As the factoids are stored in tables, it is possible to create additional factoid sets. The Navel Post Graduate School in Monterey has already created and used derivative ELICIT factoid sets. Experiment Protocol: A full experiment trial consists of 34 subjects who are randomly assigned to either the Command and Control (C2) or Edge [E] team. The experiment consists of four phases. An introduction phase that includes: An overview of the experiment’s agenda, which is delivered via PowerPoint so that it
can be adjusted for any logistical specifics. An eight-minute subject pre-experiment briefing video, which is delivered via
Windows Media Player. A practice round (round 1), in which the subjects have the opportunity to use the
software with a sample scenario. This round is designed to run for 20 minutes. A second round, which uses a different scenario. This round is designed to run for up to an hour. A wrap-up, which includes: A Web-based survey, which requires 20 minutes to complete A two-minute subject post-briefing video, which is delivered via Windows Media
Player Discussion of the experiment. Total elapsed time for the four phases of the experiment is approximately 3 ½ hours. Materials necessary to conduct the experiment – including pre-briefing videos, instructions for the experiment moderator, etc. – are available for download at the project’s companion Web site http://www.dodccrp.org/html3/elicit.html. Data Collection Procedures and Analysis Approach: The principal means of data collection for the experiments are:
Automated data collection that is integrated with the software used for the experiment
A Web-based post-experiment survey that is automatically administered by the test
software at the conclusion of an experiment trial Notes made by the subjects Observations/notes by the moderators and proctors. Task Difficulty: The goal had been to make a task that took a reasonable amount of time (e.g., one hour) and required inter-subject interactions. Additionally, the objective was to avoid making the purely cognitive aspects so difficult that the intelligence and information-managing aspects of the task would become the predominant criterion for success. Our intent was to measure organizational effectiveness, not individual IQ. While it is possible to discuss task difficulty in the abstract (i.e., presuming complete knowledge of all factoids) in practice we found that even after a full hour (50 minutes after all factoids have been distributed), full diffusion of all factoids did not occur. For example, in the June 22 Edge trial, two important factoids were not posted. As a consequence, many subjects never received all the information necessary to correctly identify all aspects of the adversary attack. At the conclusion of the pre-tests with live subjects, subjects were very interested in discussing the experience, conditions under which their performance could be improved and how organization impacts performance. Several persons in the discussion felt that the experience of participating in the experiment and subsequent discussions would be useful as part of an education process on organizational design and dynamics as it brings abstract issues to life.
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APPENDIX C: Sensitivity Analysis
This appendix illustrates the results of sensitivity analysis in which the variance of social capital’s residual error term was relaxed from 0.00 to 0.45. The purpose of this procedure was to determine the robustness of our preliminary findings, and to determine whether varying the level of variance associated with social capital would substantially alter model fit and patterns of relationships contained within each cross-sectional structural model. Our results suggest that constraining the variance equal to zero provides a more conservative standard against which to test our hypotheses. Relaxing the variance left the model fit indices unchanged suggesting that our interpretation of the modeling results with variance equal to zero were appropriate and durable. Results presented in this appendix are derived from raw AMOS 16.0 output, and have only been edited to ensure the inclusion of comparable content.
Capability
Performance
Capability
Accuracy
Capability
Quality
Capability
Speed
1
Cognitive
Embeddedness
Structural
Embeddedness
Relational
Embeddedness
Social
Capital
.45
res1-1
1
1
205
Analysis Summary Maximum Likelihood Estimates – Measurement Interval One
Result (Default model)
Minimum was achieved Chi-square = 43.962 Degrees of freedom = 38 Probability level = .234
Regression Weights: (Group number 1 - Default model)
Estimate
Standardized Estimate
S.E. C.R. P
Social Capital <--- Structural Embeddedness -.300 -.330 .147 -2.040 .041 Social Capital <--- Cognitive Embeddedness -.246 -.263 .157 -1.563 .118 Social Capital <--- Relational Embeddedness .786 .763 .166 4.719 *** Capability Performance <--- Social Capital 1.000 .688
ID WHAT <--- Capability Accuracy .854 .598 .147 5.810 *** ID WHERE <--- Capability Accuracy .811 .570 .146 5.570 *** ID WHEN <--- Capability Accuracy .370 .337 .108 3.411 ***
ID WHERE .185 -.080 -.064 .352 .371 .000 .570 ID WHAT .194 -.084 -.067 .369 .389 .000 .598 ID WHO .223 -.097 -.077 .425 .448 .000 .689
208
Model Fit Summary
CMIN
Model NPAR CMIN DF P CMIN/DF Default model 28 43.962 38 .234 1.157 Saturated model 66 .000 0
Independence model 11 473.344 55 .000 8.606
RMR, GFI
Model RMR GFI AGFI PGFI Default model .074 .943 .900 .543 Saturated model .000 1.000
Independence model .442 .544 .452 .453
Baseline Comparisons
Model NFI
Delta1 RFI
rho1 IFI
Delta2 TLI
rho2 CFI
Default model .907 .866 .986 .979 .986 Saturated model 1.000
1.000
1.000
Independence model .000 .000 .000 .000 .000
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE Default model .035 .000 .073 .699 Independence model .242 .222 .262 .000
209
Analysis Summary Maximum Likelihood Estimates – Measurement Interval Two
Result (Default model)
Minimum was achieved Chi-square = 58.408 Degrees of freedom = 39 Probability level = .024
Regression Weights: (Group number 1 - Default model)
Estimate Standardized Estimate S.E. C.R. P
Social Capital <--- Structural Embeddedness -.223 -.284 .123 -1.809 .070 Social Capital <--- Cognitive Embeddedness .636 .797 .200 3.183 .001 Social Capital <--- Relational Embeddedness -.307 -.387 .195 -1.573 .116 Capability Performance <--- Social Capital 1.000 .691
ID WHERE -.180 -.132 .370 .673 .319 .000 .745 ID WHAT -.165 -.121 .340 .618 .293 .000 .684 ID WHO -.163 -.119 .335 .608 .289 .000 .673
212
Model Fit Summary
CMIN
Model NPAR CMIN DF P CMIN/DF Default model 27 58.408 39 .024 1.498 Saturated model 66 .000 0
Independence model 11 692.108 55 .000 12.584
RMR, GFI
Model RMR GFI AGFI PGFI Default model .084 .928 .878 .548 Saturated model .000 1.000
Independence model .486 .453 .344 .378
Baseline Comparisons
Model NFI
Delta1 RFI
rho1 IFI
Delta2 TLI
rho2 CFI
Default model .916 .881 .970 .957 .970 Saturated model 1.000
1.000
1.000
Independence model .000 .000 .000 .000 .000
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE Default model .062 .023 .093 .261 Independence model .299 .279 .319 .000
213
Analysis Summary Maximum Likelihood Estimates – Measurement Interval Three
Result (Default model)
Minimum was achieved Chi-square = 38.391 Degrees of freedom = 40 Probability level = .543
Regression Weights: (Group number 1 - Default model)
Estimate Standardized Estimate S.E. C.R. P
Social Capital <--- Structural Embeddedness -.112 -.154 .115 -.977 .329 Social Capital <--- Cognitive Embeddedness .618 .832 .235 2.636 .008 Social Capital <--- Relational Embeddedness -.481 -.636 .232 -2.079 .038 Capability Performance <--- Social Capital 1.000 .735
ID WHERE -.261 -.063 .341 .558 .110 .000 .569 ID WHAT .002 .000 -.002 -.004 -.001 .000 -.004 ID WHO -.284 -.069 .371 .608 .119 .000 .619
216
Model Fit Summary
CMIN
Model NPAR CMIN DF P CMIN/DF Default model 26 38.391 40 .543 .960 Saturated model 66 .000 0
Independence model 11 584.295 55 .000 10.624
RMR, GFI
Model RMR GFI AGFI PGFI Default model .066 .951 .920 .577 Saturated model .000 1.000
Independence model .455 .579 .494 .482
Baseline Comparisons
Model NFI
Delta1 RFI
rho1 IFI
Delta2 TLI
rho2 CFI
Default model .934 .910 1.003 1.004 1.000 Saturated model 1.000
1.000
1.000
Independence model .000 .000 .000 .000 .000
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE Default model .000 .000 .057 .909 Independence model .272 .252 .292 .000
217
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