Responses to Organizational Surprises in Startups: The Impact of Improvisation and Memory on Response Outcomes Yan Gong The Paul Merage School of Business University of California, Irvine Irvine, CA 62697 Tel: (949) 824-8544 e-mail: [email protected]Ted Baker College of Management North Carolina State University Raleigh, NC 27695 Tel: (919) 513-7943 e-mail: [email protected]Dale Eesley Management Department University of Toledo Toledo, OH 43606 Tel: (419) 530-2643 e-mail: [email protected]Anne S. Miner School of Business University of Wisconsin – Madison 975 University Avenue Madison, WI 53706 Tel: (608) 263-4143 e-mail: [email protected]February 10, 2008 The authors thank Mary Crossan, Tim Pollock and Dusya Vera for their helpful contributions to this work. Earlier versions of this paper were presented at Harvard University, New York University, Babson Entrepreneurship Conference, Academy of Management Conference, INFORMS/Organization Science Conference, and West Coast Technology Entrepreneurship Symposium. We also thank the National Science Foundation Division of Decision, Risk and Management Science Division (Grant #: 0132827), and interview participants for their generous assistance with this project.
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Responses to Organizational Surprises in Startups:
The Impact of Improvisation and Memory on Response Outcomes
The authors thank Mary Crossan, Tim Pollock and Dusya Vera for their helpful contributions to this work. Earlier versions of this paper were presented at Harvard University, New York University, Babson Entrepreneurship Conference, Academy of Management Conference, INFORMS/Organization Science Conference, and West Coast Technology Entrepreneurship Symposium. We also thank the National Science Foundation Division of Decision, Risk and Management Science Division (Grant #: 0132827), and interview participants for their generous assistance with this project.
1
Responses to Organizational Surprises in Startups:
The Impact of Improvisation and Memory on Response Outcomes
ABSTRACT
This paper offers a conditional framework of improvisation, in a context of
organizational responses to surprise events. We propose that two key factors related to organizational knowledge use will shape whether a specific response to a surprise will have value to the organization. First, we argue that intermediate levels of improvisation during responses create conflicts on knowledge deployment that reduce the chances of an effective response. In contrast, both lower and higher levels of improvisation will have a relatively more positive impact on organizational outcomes. Second, the organization’s direct and indirect memory represents a reservoir of potential activities and interpretive schemes, which in turn enhances the chances that its surprise response will have a valued outcome. Finally, we propose that the value of improvisational response is enhanced by the presence of high levels of organizational memory. We test these ideas using a sample of 141 surprise events identified from 1,725 pages of interview transcripts, over 1,000 pages of informant self-rating reports, and rater assessments of these materials. Our study contributes to theories of improvisation, organizational learning, and emerging theories of organizational surprise.
2
Several research streams highlight the importance of organizational surprises. One
recurring perspective emphasizes the potentially negative effects of surprise events and argues
that organizations should attempt to avoid surprises through careful pre-planning and
sophisticated early detection systems (Watkins & Bazerman, 2003; Weick, 1998). A second
perspective argues that surprises are unavoidable but focuses on potential longer-term benefits
that occur when the experience of surprise generates organizational learning by spurring mindful
attention to errors in shared mental models and operating assumptions (Louis, 1980; Meyer,
Gaba, & Colwell, 2005; Okhuysen & Eisenhardt, 2002; Zellmer-Bruhn, 2003). In this paper, we
tackle a third set of issues concerning organizational surprises. Like the learning literature, we
too assume that surprises are unavoidable, but we focus on organizations’ immediate responses
to surprise events and how the organization’s improvisational pattern and its memory level shape
the outcome of such responses.
We define surprise as an event that is recognized as unexpected by a focal organization
(Louis, 1980). This definition is consistent with prior work that emphasizes the material aspects
of surprises, and is distinct from work that emphasizes cognitive or emotional states (Harrison &
March, 1984; Schutzwohl, 1998). We propose that two key factors related to organizational
knowledge use will shape whether a specific response to a surprise will have value to the
organization. First, we argue that intermediate levels of improvisation during responses create
conflicts on knowledge deployment that reduce the chances of an effective response. In contrast,
both lower and higher levels of improvisation will have a relatively more positive impact on
organizational outcomes. Second, the organization’s direct and indirect memory represents a
reservoir of potential activities and interpretive schemes, which in turn enhances the chances that
its surprise response will have a valued outcome. Finally, we propose that the value of
improvisational response is enhanced by the presence of high levels of organizational memory.
3
Our work contributes to theories of improvisation and organizational learning. The
increased scholarly attention to improvisation so far has revealed its potential complex
manifestations and impact on organizations, but also raised cautionary flags about how little
systematic evidence about its origins, dynamics or impacts in an organizational setting (Hatch,
1997; Miner, Bassoff, & Moorman, 2001; Levinthal & Rerup, 2006). Our study intends to extend
this important line of research by developing testing a conditional theory of improvisation. That
is, we tackle the question of when an improvisational generates more value in response to a
surprise event, in the presence of varying levels of organizational memory. Our study also
advances theory about organizational surprises.
We examine the proposed framework in a sample of one hundred forty one surprises in
thirty-one firms drawing on interview data, informant self-reporting data instruments, research
team action identification, and variable coding based on 1,725 pages of transcripts. Consistent
with our theories of the value of very low and very high levels of improvisation, we find a
curvilinear pattern in which intermediate levels of improvisation harms outcomes. The total
pattern of findings also supports a conditional model of improvisation in which higher level of
organizational memory helps drive value out of improvisation activities in response to surprise
events.
THEORY AND HYPOTHESES
Research Setting – Surprise Events Experienced by New Firms
In this paper, we focus on responses to surprises, defined as events that are recognized as
unexpected (Louis, 1980; Baker, Miner, & Eesley, 2003). Prior work has examined the impact of
surprise events on individuals, groups, industries, armies and even non-human subjects such as
information systems (Cunha, Kamoche, & Clegg, 2005; Cohen & Axelrod, 1984; Schutzwohl,
1998). In this study, we focus on the organizational level and examine how differences in
4
organizational memory and how it is deployed in response to surprise events influence an
organization’s satisfaction with the effectiveness of its own response. In this context, a surprise is
an event that is recognized as unexpected by the focal organization.
Prior studies of surprise have highlighted the importance of clearly delineating the chain
of events that will be examined (Harrison & March, 1984; Mendonca, 2005; Vanhamme, 2000).
For this study, we analyze the sequence of events into four elements: (1) a surprise event, (2) the
recognition/realization of the event by the organization, (3) the organization’s response to the
surprise event, and (4) the organization’s assessment of the immediate outcome of that response.
Our focus is on the crucial sub-processes that determine how an organizations existing body of
knowledge and how the organizations deploys that knowledge in response to a surprise event
shapes its satisfaction with the near-term outcome of its response.
Unlike other important work on the role of surprise in various social systems, we do not
examine precursors to organizational surprise, such as environmental jolts (Meyer 1980; Sine &
David, 2003), interruption (Zellmer-Bruhn, 2003), threat (Staw et al., 1981), and crisis (Kim,
1998; Lin et al., 2006) all offer contexts where surprise events may occur. Our work
complements and extends this general body of work because we examine the outcomes of an
organization’s specific response to a given surprise. Our approach implies that fairly local
conditions in terms of the organization’s own memory, the strategic level of the surprises and the
34
degree of improvisation during a given response can play a role in the outcomes of responses.
These in turn may influence the long-term trajectories of adaptation. Exploring such possibilities
offers an important next step in research on knowledge deployment and organizational surprises.
35
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ar h
ad b
red
her
. Q
uit
e a
big
dif
fere
nce
.
NP
artn
ersh
ip
IST
01
Com
pet
ito
r p
rici
ng
cut
34:2
2A
fter
th
e fo
urt
h q
uar
ter
last
yea
r th
ey w
ere
real
ly i
n p
ain
. I
mea
n, al
l th
e co
mpo
nen
t co
mp
anie
s w
ere
feel
ing a
lo
t o
f
pai
n. B
ut
Com
p c
hose
to
dea
l w
ith t
hat
by
dra
stic
ally
lo
wer
ing t
hei
r co
nsu
ltin
g b
ill
rate
s. I
mea
n,
lik
e w
her
e th
ey w
ere
chop
pin
g t
hem
in
hal
f. I
mea
n, th
ey w
ere
go
ing
fro
m e
igh
ty s
om
e do
llar
s an
ho
ur
to $
40
an h
ou
r. A
nd
th
ey s
tart
ed
doin
g t
hin
gs
lik
e, i
f y
ou
bri
ng i
n t
his
con
sult
ant
we'
ll g
ive
yo
u t
his
co
nsu
ltan
t fo
r fr
ee. A
nd i
t's l
ike,
all
rig
ht,
what
do
you
do w
ith
th
at?
I m
ean,
so.
That
was
un
expec
ted
.
NC
om
pet
itio
n
MA
T0
1A
t L
ink g
oes
ou
t of
busi
nes
s
19:2
8A
nd
At
Lin
k w
ent
ou
t o
f bu
sin
ess
in A
pri
l o
f la
st y
ear.
S
o,
we
dea
lt w
ith
the
par
tner
s le
avin
g,
and
th
en t
wo
mo
nth
s
late
r, A
t L
ink g
oes
into
ban
kru
ptc
y a
nd e
ver
yb
od
y t
urn
s off
th
eir
pip
es. A
nd
th
en s
udd
enly
we
hav
e no
In
tern
et a
cces
s
in o
ur
off
ice.
NO
per
atio
nal
LU
H01
Acq
uir
ed m
ajo
r
clie
nt
4:0
4Y
eah
. I
mea
n, a
lot
of,
wel
l, o
ne
maj
or
clie
nt
was
, y
ou
kn
ow
, to
tall
y u
nex
pec
ted
. Y
ou k
no
w w
hat
I m
ean?
I m
ean
, w
e
did
n’t
rea
lly
hav
e a
mar
ket
ing p
lan
per
se,
so
we
kin
d o
f tr
y t
o d
o o
ur
thin
g.
But,
in
an
y c
ase,
yo
u k
no
w,
we’
re j
ust
sitt
ing t
her
e on
e day
and
th
is c
all
com
es a
nd s
om
ebo
dy
say
s, h
ey,
you
kn
ow
, y
ou g
uy
s m
ight
be
inte
rest
ed i
n t
his
. W
e
go o
ver
ther
e, a
nd
lik
e th
ree
day
s la
ter
we
hav
e th
is c
on
trac
t, y
ou
kno
w,
a b
ig o
ne,
rel
ativ
ely
sp
eak
ing
.You
kn
ow
what
I
mea
n?
And
so i
t’s
like,
wel
l, o
h g
oo
d,
yo
u k
now
wh
at I
mea
n, b
ut
it w
as v
ery r
and
om
.It
was
n’t
at
all
pla
nn
ed.
PS
ales
Examples of Surprises
TABLE 1
45
TABLE 2 - Coding Heuristics for Identifying Surprise
Descriptions
Definition of surprise A surprise is an event that is subjectively recognized as unexpected. Expansion: This may happen when some outcome is anticipated, and the actual outcome differs from the anticipation. The difference might be positive, negative, or neutral. A surprise may also occur when there was no conscious anticipation of a particular outcome other than an expectation that things would continue unchanged.
Process of surprise identification
The first identification of surprises was done by informants during substantial interviews. During each interview, the informant identifies surprises in “real time”, and interviewer writes a description of each surprise on a data sheet. To identify surprises for later coding, coders first looks at the surprises on the interview survey. Coders then read through the transcript to find the text that describes the data sheet surprises. Coders then decide if the text, in fact, provides evidence of a surprise as defined above. For now, we will disregard other things that may seem like surprises that may be identified in the coding process.
It’s a surprise if
Prior expectations are violated.
Includes instances where expectations are directly stated, and an opposing occurrence (or fact that indicates an opposing occurrence) is indicated – regardless of the interviewee(s) awareness of this as a surprise. Includes instances where expectations are diffuse (i.e. if one expects the status quo but the status quo is disrupted).
Key words to look for “ends up”, “it turns out”, “we found”, “find”, “couldn’t find”, “we got hit”, “we got faced”, “ends up”
It’s tied to a specific event, or is a specific event.
Includes instances where a more specific surprise is embedded within a larger surprise. We are particularly interested in identifying technical and scientific surprises embedded within other surprises.
“We found out he wasn’t as good as maybe he thought he was, or anybody else” (1st surprise, InfTech 8:14) “They reported it as a possible pregnancy of a nuclear transfer…and it turned out the boar had bred her” (another, more specific embedded in 1st surprise)
Surprises are not
Lessons learned Subjective perceptions of knowledge gained and “lessons learned” that respondents indicate has surprised them over the course of doing business.
“We realized the best way to find clients is through networking”. Or “We were surprised how easy it is to incorporate”.
Pattern recognition Respondent indicates a general pattern noticed over time.
“we’ve found is there are a lot of state contracts that you can get and a lot of them are what, you know, some people called wired”)
Uncertain results versus unexpected events.
Events that occur after uncertainty is expressed versus an indication of violated expectations (or no prior expectation).
“We had negotiations going on …two of them simultaneously. It’s kind of a horse race to see who we’d end up with, or who would end up with us…We ended up working with” (one of the firms negotiation with).
Instances where teams violates their own plan.
This confuses a surprise with a behavioral change, and it potentially confuses a surprise with the dependent variable.
There is not enough
information to code pre
or post behavior
This type of surprise can be identified as “not codable”.
46
TABLE 3
Coding Scale of Improvisation
Codin
g S
cale
of
Imp
rovis
atio
n
1
2
3
4
5
6
7
Non Improvisation
L
ittl
e
Much
Full Improvisation
. Pure planning
. Pure execution of a plan or
routine
. N
egli
gib
le
. L
oose
pla
nnin
g
and/o
r lo
ose
ex
ecuti
on
. C
annot
rule
out
impro
vis
atio
n
. M
ore
Non
impro
vis
atio
n
than
im
pro
vis
atio
n
. G
lim
mer
of
impro
vis
atio
n
. B
alan
ce o
f im
pro
vis
atio
n
and n
on
impro
vis
atio
n
. M
ore
im
pro
vis
atio
n
than
non
impro
vis
atio
n
. M
uch
more
im
pro
vis
atio
n
than
non
impro
vis
atio
n
. S
ignif
ican
t am
ount
of
impro
vis
atio
n
. Full improvisation
. “Action followed a strict
plan/routine as it was taken.”
. “Strictly followed out plan in
carrying out this action.”
. “Made it up as they went
along.”
. “Figured out action as they
went along.”
. “Ad-libbed action.”
ICC(2,5) = .805
47
TABLE 4
Descriptive Statistics and Correlations
Variable
Mean
S D
12
34
56
78
9
1.
O
utc
om
e of
Surp
rise
Res
po
nse
0.9
11.5
71
2.
In
dust
ry0
.92
0.2
70
.05
1
3.
F
irm
Siz
e1
.93
1.0
00
.05
-0.1
01
4.
S
uff
icie
nt
Tim
e at
th
e T
ime
of
the
Surp
rise
3.5
21.8
00
.11
-0.1
6*
0.0
51
5.
S
uff
icie
nt
Mon
ey a
t th
e T
ime
of
the
Surp
rise
3.5
61.5
90
.09
-0.1
00
.27
**
0.4
6**
1
6.
A
ver
age
Fo
un
der
Edu
cati
on
Lev
el4
.61
2.0
4-0
.17
*0.0
00
.13
†0.0
40
.02
1
7.
Aggre
gat
ed F
ound
er P
rio
r S
tart
-ups
1.8
62.4
7-0
.04
0.2
3*
*-0
.08
0.0
40
.10
0.1
9**
1
8.
S
trat
egic
Lev
el o
f S
urp
rise
0.7
61.6
8-0
.07
-0.0
80
.09
-0.0
5-0
.23
**
0.1
00.0
01
9.
P
osi
tive
Surp
rise
0.1
10.3
10
.18
*0.1
00
.02
0.0
00
.04
0.0
40.0
20.1
8*
1
10. Improvisation
3.3
41.2
3-0
.02
-0.0
5-0
.05
-0.1
2-0
.19
*0.0
1-0
.12
†-0
.09
-0.0
9
11. Improvisation Squared
12
.68
9.0
30
.01
-0.0
4-0
.02
-0.1
3*
-0.1
8*
-0.0
1-0
.15
*-0
.08
-0.0
7
12. Firm Age
22
.82
20.1
4-0
.24
**
-0.1
00
.17
*0.0
30
.02
0.1
4*
0.1
4*
-0.0
7-0
.16
*
13. Founder Experience
3.3
20.8
70
.10
0.1
3†
0.0
5-0
.09
-0.0
3-0
.08
0.5
7**
0.2
0*
0.1
4*
14. Improvisation x Firm Age
82
.48
77.4
2-0
.20
**
-0.1
10
.13
†0.0
0-0
.07
0.1
5*
0.0
8-0
.03
-0.1
6*
15. Improvisation Squared x Firm Age
317
.62
38
0.2
4-0
.14
†-0
.11
0.1
10.0
1-0
.07
0.1
00.0
4-0
.02
-0.1
4*
16. Improvisation x Founder Experience
10
.89
4.6
80
.00
0.0
60
.00
-0.1
2-0
.14
†-0
.10
0.2
9**
0.0
8-0
.03
17. Improvisation Squared x Founder Experience
40
.46
29.3
80
.00
0.0
30
.02
-0.1
3-0
.16
*-0
.09
0.0
70.0
3-0
.06
Variable
Mean
S D
10
11
12
13
14
15
16
17
10. Improvisation
3.3
41.2
31
11. Improvisation Squared
22
.82
20.1
40
.98
**
1
12. Firm Age
3.3
20.8
70
.04
0.0
41
13. Founder Experience
1.8
62.4
7-0
.10
-0.1
20
.29
**
1
14. Improvisation x Firm Age
82
.48
77.4
20
.43
**
0.4
2*
*0
.87
**
0.2
5**
1
15. Improvisation Squared x Firm Age
317
.62
38
0.2
40
.60
**
0.6
1*
*0
.67
**
0.1
5†
0.9
4*
*1
16. Improvisation x Founder Experience
10
.89
4.6
80
.75
**
0.7
0*
*0
.27
**
0.5
5**
0.5
3*
*0.6
1**
1
17. Improvisation Squared x Founder Experience
40
.46
29.3
80
.89
**
0.8
9*
*0
.18
*0.2
6**
0.5
1*
*0.6
7**
0.9
3**
1
a n =
141
.
†
p
< .
10
*
p <
.0
5
**
p <
.0
1
48
TABLE 5
Ordinary Least Square Models with Outcomes of Responses to Surprises as the Dependent Variable
MODEL 1
MODEL 2
MODEL 3
MODEL 4
MODEL 5
MODEL 6
MODEL 7
MODEL 8
MODEL 9MODEL 10
Con
tsta
nt
2.5
00*
2.9
40
*4
.362
**
1.2
61
2.8
55†
4.0
41*
5.8
77*
*3
.753
*4.4
43*
*5
.155
*
(1.1
44)
(1.2
15
)(1
.21
0)
(1.4
67
)(1
.393)
(1.4
56)
(1.7
85
)(1
.60
8)
(1.4
24
)(1
.855)
Ind
ust
ry-0
.724
-0.7
66
-0.7
37
-0.8
59
-0.8
43
-0.8
76
-0.8
15
-0.8
39
-0.8
28
-0.8
22
(0.7
03)
(0.6
84
)(0
.68
8)
(0.7
72
)(0
.771)
(0.8
19)
(0.7
69
)(0
.76
4)
(0.7
67
)(0
.784)
Fir
m S
ize
0.3
07
0.3
05
0.2
70
0.3
18
†0.2
78
0.2
67
0.2
46
0.2
70
0.2
70
0.2
49
(0.2
19)
(0.2
24
)(0
.21
6)
(0.1
85
)(0
.183)
(0.1
70)
(0.1
62
)(0
.18
3)
(0.1
84
)(0
.166)
Suff
icie
nt
Tim
e at
th
e T
ime
of
the
Su
rpri
se0.0
70
0.0
68
0.0
79
0.1
19
0.1
28
0.1
09
0.0
98
0.1
26
0.1
27
0.0
97
(0.1
12)
(0.1
09
)(0
.10
6)
(0.1
03
)(0
.099)
(0.0
93)
(0.0
92
)(0
.10
0)
(0.1
01
)(0
.091)
Suff
icie
nt
Mo
ney
at
the
Tim
e o
f th
e S
urp
rise
0.0
27
0.0
15
0.0
08
-0.0
19
-0.0
31
-0.0
46
-0.0
47
-0.0
31
-0.0
33
-0.0
47
(0.1
25)
(0.1
19
)(0
.11
7)
(0.1
07
)(0
.104)
(0.1
06)
(0.0
98
)(0
.10
4)
(0.1
04
)(0
.098)
Av
erag
e F
ou
nd
er E
du
cati
on
Lev
el-0
.37
5*
-0.3
81
*-0
.36
4*
-0.2
97**
-0.2
83
**
-0.2
97*
*-0
.28
4**
-0.2
83
**
-0.2
78*
*
-0.2
87*
(0.1
34)
(0.1
33
)(0
.12
9)
(0.1
06
)(0
.097)
(0.0
95)
(0.0
93
)(0
.09
6)
(0.0
98
)(0
.097)
Agg
regat
ed F
oun
der
Pri
or
Sta
rt-u
ps
-0.0
10
-0.0
13
0.0
01
-0.1
13
-0.1
06
-0.1
12
-0.1
16
†-0
.10
0-0
.103
-0.1
19†
(0.0
52)
-0.0
51
(0.0
51)
(0.0
71
)(0
.068)
(0.0
67)
(0.0
66
)(0
.06
8)
(0.0
71
)(0
.069)
Str
ateg
ic L
evel
of
Surp
rise
-0.1
29
-0.1
29
-0.1
22
-0.1
82
†-0
.17
6-0
.180
-0.1
80
†-0
.17
1-0
.168
-0.1
85†
(0.1
13)
(0.1
13
)(0
.11
6)
(0.1
04
)(0
.108)
(0.1
05)
(0.0
97
)(0
.10
7)
(0.1
05
)(0
.098)
Posi
tiv
e S
urp
rise
0.8
08
0.7
86
0.8
05
0.5
11
0.5
17
0.5
13
0.5
36
0.5
28
0.5
32
0.5
28
(0.5
05)
(0.5
07
)(0
.50
3)
(0.4
15
)(0
.415)
(0.4
06)
(0.3
95
)(0
.41
3)
(0.4
13
)(0
.397)
Improvisation
-0.0
92
-1.0
22
**
-0.9
65*
-1.2
46*
*-2
.42
6**
-1.2
51*
-1.7
25
†
-2
.093†
(0.0
94
)(0
.32
5)
(0.3
53)
(0.3
67)
(0.7
89
)(0
.48
9)
(0.8
90
)(1
.021)
Improvisation Squared
0.1
26
**
0.1
23
*0.1
27*
0.2
79*
*0
.132
*0.1
98
0.2
48†
(0.0
41)
(0.0
46)
(0.0
47)
(0.0
99
)(0
.04
7)
(0.1
26
)(0
.137)
Firm Age
-0.0
25
*-0
.023*
-0.0
60*
*-0
.14
6**
-0.0
23*
-0.0
23*
-0
.157
**
(0.0
11
)(0
.011)
(0.0
18)
(0.0
43
)(0
.01
0)
(0.0
10
)(0
.055)
Founder Experience
0.5
72*
0.5
84
*0.5
94*
0.6
34
*0.3
38
0.1
06
0.9
33
(0.2
67
)(0
.241)
(0.2
43)
(0.2
36
)(0
.38
0)
(0.3
84
)(0
.594)
Improvisation x Firm Age
0.0
10*
0.0
61
*0
.066
*
(0.0
05)
(0.0
25
)(0
.032)
Improvisation Squared x Firm Age
-0.0
07
†-0
.007†
(0.0
03
)(0
.004)
Improvisation x Founder Experience
0.0
69
0.2
23
-0.1
32
-0.0
85
(0.2
63
)(0
.385)
Improvisation Squared x Founder Experience
-0.0
22
0.0
12
(0.0
39
)(0
.052)
Any m
igra
tion
Obse
rvat
ion
s1
41
14
1141
141
14
11
41
14
1141
141
14
1
F-t
est
(for
over
all
mod
el f
itn
ess)
2.1
7†
2.8
3*
8.5
1**
3.7
3**
7.6
9*
*8.5
4**
10
.23*
*8
.73*
*12
.60*
*13
.25**
Ad
just
ed R
-Squ
ared
0.1
23
0.1
21
0.1
39
0.1
88
0.2
01
0.2
12
0.2
18
0.1
97
0.1
91
0.2
07
∆ a
dj.
R2 (
vs.
bas
elin
e M
odel
1)
-0.0
02
0.0
16
0.0
55
0.0
78
0.0
83
0.0
89
0.0
68
0.0
62
0.0
84
∆ a
dj.
R2 (
for
added
var
iab
les)
-0.0
02
0.0
18
0.0
55
0.0
62
0.0
11
0.0
06
-0.0
04
-0.0
06
-0.0
05
F-t
est
(for
added
var
iable
s)0.9
59
.44**
3.5
6*
4.1
0*
4.3
2*
4.2
0†
0.6
60
.31
0.1
7
(vs.
mod
el 1
)(v
s. m
odel
2)
(vs.
mod
el 1
)(v
s. m
odel
3)
(vs.
mo
del
5)
(vs.
mod
el 6
)(v
s. m
odel
5)
(vs.
mo
del
8)
(vs.
model
6)
† p
< .
10;
* p
< .
05
; ** p
< .0
1 (
two-t
ail
test
s). S
tan
dar
d e
rrors
are
adju
sted
fo
r cl
ust
erin
g o
n f
irm
s.
49
FIGURE 1
Predicted Second-order Improvisation Effect on Perceived outcome
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Improvisasion
Perceived Outcome
Firm
Age (
mean +
1 S
.D.)
Firm
Age (
mean)
Firm
Age (
mean -
1 S
.D.)
50
-.1-.08-.06-.04-.020.02.04.06
Marginal Effect of Firm Age
01
23
45
67
Impro
vis
ation
Marg
inal E
ffect of F
irm
Age
95%
Confidence Inte
rval
FIGURE 2
The Marginal Effect of Firm Age on Perceived Outcome
(Bas
ed o
n M
odel
6)
51
FIGURE 3
The Marginal Effect of Firm Age on Perceived Outcome
The investigation of conditional effects in models containing interaction terms is based on the corresponding partial derivative of the full model that includes the interaction term. The following section outlines the derivative equations used to calculate regression coefficient estimates for different values of moderator variables (Brambor et al., 2006; Cohen et al., 2003). The fully specified Model 6 is:
Marginal effect of improvisation on outcome. The change in the dependent variable Surprise Perceived outcome for a marginal change of Post-surprise Improvisation for firm i is:
Standard errors of the marginal change can be derived with the following formula: With formula (2) and (3), we substitute the relevant values of Post-surprise Improvisation
and Age at the mean, a standard deviation below, and a standard deviation above the mean to calculate regression coefficient estimates (Aiken & West, 1991; Brambor, Clark, & Golder, 2005; Jaccard et al., 1990).
[∂(OUTCOME)/ ∂(IMP) | IMP=low, AGE=low] = -0.601** (0.172) [∂(OUTCOME)/ ∂(IMP) | IMP=low, AGE=mean] = -0.447* (0.166) [∂(OUTCOME)/ ∂(IMP) | IMP=low, AGE=high] = -0.293 (0.190) [∂(OUTCOME)/ ∂(IMP) | IMP=mean, AGE=low] = -0.292* (0.100) [∂(OUTCOME)/ ∂(IMP) | IMP=mean, AGE=mean] = -0.138 (0.092) [∂(OUTCOME)/ ∂(IMP) | IMP=mean, AGE=high] = 0.159 (0.133) [∂(OUTCOME)/ ∂(IMP) | IMP=high, AGE=low] = 0.016 (0.127) [∂(OUTCOME)/ ∂(IMP) | IMP=high, AGE=mean] = 0.170 (0.123) [∂(OUTCOME)/ ∂(IMP) | IMP=high, AGE=high] = 0.324* (0.158) Marginal effect of firm age on outcome. The change in the dependent variable Surprise Perceived outcome for a marginal change of Age for firm i is:
Standard errors of the marginal change can be derived with the following formula: With formula (4) and (5), we substitute the relevant values of Post-surprise Improvisation
at the mean, a standard deviation below, and a standard deviation above the mean to calculate regression coefficient estimates (Aiken & West, 1991; Brambor, Clark, & Golder, 2005; Jaccard et al., 1990). The corresponding conditional analyses are presented as: