1. business and industrial
2. energy
3. renewable energy

The Dynamics of Energy in
Entrepreneurial Groups
Andrew P. Knight
Olin Business School
Washington University in St. Louis
knightap@wustl.edu | http://apknight.org
Sigal G. Barsade
The Wharton School
University of Pennsylvania
barsade@wharton.upenn.edu
This project was supported by a Kauffman Founda8on research grant and funding from Wharton’s Center for Leadership & Change Management. The Two-Dimensional Circumplex Model of Affect
High Energy
tense
alert
nervous
excited
stressed
elated
upset
happy
Unpleasant
Pleasant
sad
contented
depressed
serene
lethargic
relaxed
fatigued
calm
Low Energy
Larsen & Diener, 1992; Feldman Barrett
& Russell, 1998; Russell, 1980
Research on affect in organizational behavior has focused mostly on valence
High Energy
Activated
Negative
Affect
Activated
Positive
Affect
Unpleasant
Pleasant
Low Energy
Feldman Barrett & Russell, 1999;
Watson & Tellegen, 1985
Energy is largely overlooked in the literature on affect in groups and teams
Energy Valence Roughly 5% of published studies of affect in groups (N = 73) report results for energy Barsade, 2002; Bartel & Saavedra, 2000; Lehmann-­‐Willenbrock et al., 2011; Sessa, 1996 Energy likely plays a role in group dynamics
•  Energy is a core dimension of human experience
–  Without connecting this dimension to group dynamics, our
understanding of groups and of affect are incomplete
•  Energy is implicated as a mechanism for phenomena (e.g.,
creativity, responses to diversity) relevant for groups researchers
–  We know little about how the group context influences energy
–  We know even less about how individuals’ energy compile to influence
group processes and outcomes
•  The work group is likely among the most complex, stimulating, and
energy-provoking contexts in the workplace
Conceptualizing energy in groups
The Psychophysiological Tradition
✓ “…the release of potential
energy, stored in the tissues of
the organism, for use in activity
or response.” (Duffy, 1951, p. 32)
Excitation of the sympathetic
nervous system (Schachter &
Singer, 1962)
“To generations of first-year medical
students, it is described through the
feeble but obligatory joke of mediating
the four F's of behavior - flight, fight,
fright, and sex. It is the archetypal
system that is turned on when life gets
exciting or alarming.”
Sapolsky, Why Zebras Don’t Get Ulcers
The Positive Organizational Scholarship Tradition
“Energy…is the feeling that one is eager to act and capable of acting…an affective
experience similar to Watson, Clark, and Tellegen’s (1988) ‘positive affect’” (Quinn
& Dutton, 2005, p. 36)
“We define collective energy (henceforth productive energy) as the shared
experience and demonstration of positive affect, cognitive arousal, and agentic
behavior…” (Cole et al., 2011)
Purpose and Key Research Questions
The purpose of this research is to begin filling a gap in our
understanding of groups by developing and testing a conceptualization
of the dynamics of energy in groups
Key Research Questions
1.  What are the origins of and how does energy flow among the
members of work teams?
2.  To what extent does the energy of a group flow across its
boundaries, impacting the energy of outsiders?
3.  How does contagion in energy influence outsiders’ perceptions of
group effectiveness?
Research Setting
3-day Team-Based Entrepreneurship Competition
Day 1
Day 2
Day 3
Pitch ideas and form teams
Work in team on new venture idea
Refine and present new venture idea
• 
• 
• 
• 
60 second elevator pitches
Subset of ideas chosen for
further development
Organic team formation
around ideas
Begin working as a team on
idea
• 
• 
• 
• 
Further develop idea
Design and build prototype
of product or service
Perform customer validation
Develop business model
• 
• 
• 
Continue developing idea
along multiple dimensions
Design business model
presentation
Present new venture idea to
panel of judges
Procedure & Data Sources
Physiological Measures
Survey Measures
• 
Team
Members
Judges
• 
Administered on the 3rd day
-  Individual background information
-  Measures of team dynamics
Participation from 53 teams (96%)
across 5 independent events
• 
Wristband devices applied ~30 minutes
prior to team business plan presentation
• 
Participation from 53 teams (96%)
• 
189 individuals wore devices during
presentations (77% of survey sample)
• 
Responses from 246 individuals (84%)
• 
Background survey administered before
team business plan presentations began
• 
Wristband devices applied ~30 minutes
before business plan presentations
• 
Post-presentation survey completed
after each team presentation
• 
• 
15 out of 16 judges participated (94%)
across 5 events; 3 judges per event
-  15 background surveys
-  165 post-presentation surveys
15 judges wore devices throughout
presentations (100% of survey sample);
3 judges per event
Survey Measures
•  Controls
–  Team familiarity (% of members who knew each other)
–  Self rated team ability (3 items from Edmondson, 1999, 0.80)
•  “Most people in this group have the ability to solve problems that come up in our work.”
•  α = 0.85, ICC(1) = 0.31**, ICC(2) = 0.67, rwg(j) = 0.84
•  Team member constructs
–  Team cohesion (3 items from Dobbins et al., 1986)
•  “If given the chance, I would choose to leave this group and join another.”
•  α = 0.85, ICC(1) = 0.38**, ICC(2) = 0.73, rwg(j) = 0.96
•  Judge constructs
–  State affect (Affect grid, Russell et al., 1989)
–  Idea creativity (2 items, α = 0.85)
•  “This group presented an idea that is {novel, useful}”
–  Overall team performance (3 items, α = 0.86)
•  “This group performed at a high level”
Physiological Measures
Wristband device samples three
indicators eight times per second:
•  Electrodermal activity
•  Body surface temperature
•  3-dimensional physical motion
Averaged samples to the second
level to smooth noise and scaled
EDA values within individuals
(Ben-Shakhar, 1985)
Used recurrence analysis to
measure contagion of EDA among
team members and with judges
(Marwan et al., 2007)
Electrodermal Activity
Average Energy in Teams over Time
0.75
0.25
-0.25
-0.75
-10
-8
-6
-4
-2
0
2
Time (in minutes)
4
6
8
10
Average Energy in Teams over Time
Electrodermal Activity
0.92
0.42
-0.08
-0.58
-10
-8
-6
-4
-2
0
2
Time (in minutes)
4
6
8
10
Key Findings: Origins and Outcomes of Energy
•  There was significant contagion among team members’ energy
–  MDET within teams > MDET between teams (B = 0.97, p < 0.01)
•  Team cohesion influenced team energy dynamics
–  Cohesive teams showed greater contagion (B = 0.29, p < 0.05)
–  The members of cohesive teams exuded higher levels of energy during the
presentation (B = 0.43, p < 0.01)
•  There was significant contagion between teams and judges
–  MDET with presenting team > MDET with on deck teams (B = 0.65, p < 0.05)
•  Team energy dynamics influenced judge perceptions of teams
–  Energy level of team not related to judge perceptions
–  Energy contagion from team to judges, yielding synchrony, related to:
•  Judge self-reported pleasantness (B = 0.20, p < 0.05)
•  Judge ratings of idea creativity (B = 0.13, p = 0.08)
•  Judge ratings of team performance (B =0.12, p = 0.07)
Implications for theory and research
•  Energy is an important dimension to include in theories of affective
dynamics in groups and teams
–  Core dimension of human experience that has been virtually ignored
–  Intersection of interpersonal dynamics and physiological response
•  Contagion (or, coupling / synchronicity) in affect among team
members may be an important independent dimension of interest
–  Vast majority of theory and research emphasizes amplitude
–  Scant research examines variance
– 
Miniscule work on coupling of affective states over time among organizational members
•  Affective dynamics spillover into the organizational environment
–  Team boundaries are permeable
–  Important to understand the interplay between teams and stakeholders
Implications for practice
•  Valuable to understand the signal sent by a group or team to
external stakeholders
–  Coupled energy – not energy level – between employees and
consumers may be most critical during interactions
–  May need different kinds of training for group-on-one or group-ongroup interactions, versus one-on-one encounters
•  Incredible potential of emerging technologies for understanding
group dynamics and consumer experiences
–  Burgeoning innovations in wearable sensors
–  Electrodermal activity, interaction patterns, EEG patterns, and more
The Dynamics of Energy in
Entrepreneurial Groups
Andrew P. Knight
Olin Business School
Washington University in St. Louis
knightap@wustl.edu | http://apknight.org
Sigal G. Barsade
The Wharton School
University of Pennsylvania
barsade@wharton.upenn.edu
This project was supported by a Kauffman Founda8on research grant and funding from Wharton’s Center for Leadership & Change Management. Analytical Approach:
Recurrence Quantification Analysis
•  Developed in the 1980s to study nonlinear dynamics
•  Initially a plot-based approach used to
understand transitions in single
systems
•  Advanced in the 1990s and early
2000s to examine coupling among
systems
–  Cross- and joint-recurrence
–  Quantification of plot characteristics
•  Used to study coupling of physiological
systems (e.g., Konvalinka et al., 2011)
Marwan et al., 2007; Webber & Zbilut, 2005 Example
Blue lines are team members on stage Red lines are team members on deck Recurrence between 2 members of different teams 210
270
time
270
210
150
150
0
30 60 90
30 60 90
0
time
330
330
390
390
450
450
510
510
Recurrence between 2 members of same team 0
30
60
90
120
180
240
time
300
360
420
480
0
30
60
90
120
180
240
time
300
360
420
480