The Effects of Physical Location on
Communication Patterns (Continued)
May 5, 2007
Some Obvious Points
P(C)
S < S
2
1
p < p
2
1
S
S3 < 1
p > p1
3
p3
p1
p2
S3
S2
Distance
S1
A Typical Grouping of Offices Around a Secretarial Area.
Same Area Converted to the 'Cave and Commons' Concept.
Office Configuration to Vary Privacy and Accessibility.
Exterior Wall
With
Window
Floor
to
Ceiling
Panels
Sliding Glass Panels
High Panels
Combining Physical & Organizational
Barriers & Bonds
The Effects and Organizational Separation as Measured in One
Organization
SAME WING
SAME FLOOR
DIFFERENT
WINGS
SAME BUILDING
DIFFERENT
FLOORS
SAME SITE
DIFFERENT
BUILDINGS
DIFFERENT
SITES
DIFFERENT
DEPARTMENTS
AND PROJECTS
SAME
DEPARTMENT
DIFFERENT
PROJECTS
SAME PROJECT
DIFFERENT
DEPARTMENTS
SAME
DEPARTMENT
AND PROJECT
0.16
0.69
0.71
0.95
0.05
0.53
0.80
___
0.05
0.60
___
___
0.02
0.35
0.33
0.50
0.002
0.15
0.23
0.38
Two Departments in Separate Locations
LOCATION I
CAA
LOCATION II
A
CAB
B
CBB
The Effect of Transferring Staff Between Locations
LOCATION I
LOCATION II
CAa
CAA
Caa
A
CaB
CAB
CAb
Cbb
a
b
Cab
CbB
B
CBB
Proportional Decrease in
Intradepartmental
Communication
Moving Staff Between Sites to Increase Interdepartmental
Communication
(Examples from Laboratories ‘H’ & ‘I’)
1
Proportion Moved
0.95
0.9
10%
10%
0.85
0.8
0.75
20%
20%
Lab 'I'
0.7
0.65
30%
40%
50%
5
7
0.6
1
3
Lab 'H'
30%
40%
9
11
50%
13
Proportional Increase in Interdepartmental
Communication
15
Proportional Decrease in
Intradepartmental
Communication
Moving Staff Between Buildings to Increase Interdepartmental Communication
(An Example from Laboratory ‘H’)
1
Proportion Moved
0.95
10%
0.9
20%
0.85
0.8
30%
0.75
40%
50%
0.7
1
1.5
2
Proportional Increase in Interdepartmental
Communication
2.5
Proportional Decrease in
Intradepartmental
Communication
Moving Staff Between Floors of a Building to Increase Interdepartmental
Communication
(An Example from Laboratory ‘I’)
1
Proportion Moved
0.9
10%
0.8
20%
0.7
30%
0.6
40%
50%
0.5
1
2
3
4
Proportional Increase in Interdepartmental
Communication
5
Communication Within a Biotech
Cluster
The Cambridge/Boston Biotechnology Cluster
•
An extensive literature has developed in recent years arguing
for the benefits of firms sharing a common technology to
cluster geographically.
– Aids in attracting specialized staff.
– May attract venture capital, suppliers, support services, etc.
•
•
Claims have also been made for the synergistic benefits of
firms sharing scientific knowledge, especially if there are
university laboratories near the cluster.
Prior studies have inferred inter-firm communication from the
evidence of co-publishing and co-patenting across firms,
however, a good amount of scientific exchange may occur that
does not appear in such publicly accessible records
– No one has ever actually measured whether less formal scientific
exchange across firms really occurs, to what degree what the
actual dynamics look like and what the results are.
Earlier Research
• As discussed earlier, we developed a
method for measuring the structure of
scientific communication networks
within firms.
• Why not adapt that method for the
study of scientific communication
among firms and other organizations.
Experimental and Control Groups
• Geographic limits of the cluster are defined in
terms of location within a limited set of postal
(Zip) code regions.
• Scientists reporting from similar Biotech firms
outside of the postal code regions of the
main study but within 100 km of Boston.
– Comparative density of communication
– Connections between the two groups
– Connections with the universities and with local
‘Big Pharma’ companies.
Communication in The Biotech Cluster
Length of connecting links is ________
inversely
proportional to the amount of communication
reported.
74
102
194
84
172
56
58
118
35
87
57
40
41
213
5
64
38
205
52
20
49
210
48
92
137
160
175
45
3 1 131
190
18
200 69 2
19
143
179 120
199
192
117
70
90
155
68
124
43
4
104 209
82
134
106
163
116
44
42
101
132
182
50
187
Figure by MIT OCW.
A Super Cluster?
74
102
194
84
172
56
58
118
35
87
5
64
40
41
38
205
52
213
199
192
20
210
70
48
137
160
175
45
3 1 131
190
18
2
69
200
19
143
179 120
49
117
92
57
90
155
68
124
43
4
104 209
82
134
163
116
44
106
42
101
132
182
50
187
Figure by MIT OCW.
Inside The Super Cluster
175
213
45
20
90
155
52
3
1
131 18
190
200
199
192
69 2
104
82
19
143
22
49
210
4
179
120
48
209
134
44
10
Figure by MIT OCW.
Where are the Universities?
Universities
175
213
45
20
90
155
52
3
1
131 18
190
200
199
192
4
69 2
104
82
19
143
22
49
210
179
120
48
209
134
44
10
= University
Figure by MIT OCW.
What About ‘Big Pharma’?
The Major Pharmaceutical Firms
• A number of ‘Big Pharma’ companies
have located R&D operations in the
region.
– Their purpose, obviously is to tap into the
network.
• Search to license candidates for their new
product pipeline.
• Search for potential acquisitions.
– Are they successful in joining the network?
Where is ‘Big Bio’?
Large Bio Firms
• Some of the Biotech firms have
grown quite large.
–How do they fit into the network
now?
‘Big Bio’
19
22
213
45
20
104
4
200
2
120
155
44
3
131
11
1
205
2
190 69 134
199
Figure by MIT OCW.
Where To From Here?
• What more can we learn?
– Analyses of the network to relate network position to firm
performance.
• Comparison between cluster ‘members’ and firms in the
control group.
• Long term growth.
– Size, valuation, etc.
• Patent filings
• Investigatory New Drug Applications
• Etc.
– Follow-up interviews to flesh out the network results.
– Advice to the many geographic regions attempting to stimulate
the growth of similar Biotech clusters.
• Is this the new model for doing R&D?
– How do individual firms capture the gains?
Level of Communication with Other
Organizations
120
100
80
60
40
20
0
4
5
6
7
8
9
Mean Distance From Other Organizations (Miles)
10
11
Where are the Universities?
Level of Communication with Other
Organizations
120
100
80
60
40
20
0
4
5
6
7
8
9
Mean Distance From Other Organizations (Miles)
10
11
Where is Big Pharma?
Level of Communication with Other
Organizations
120
100
80
60
40
20
0
4
5
6
7
8
9
Mean Distance From Other Organizations (Miles)
10
11
Where is Big Pharma?
Level of Communication with Other
Organizations
120
100
80
60
40
20
0
4
5
6
7
8
9
Mean Distance From Other Organizations (Miles)
10
11
Level of Communication with
Other Organizations
120
100
80
Other
60
Universities
Big Pharma
40
Big Bio
20
0
4
6
8
10
12
Mean Distance From Other Organizations (Miles)
14
Level of Communication with
Other Organizations
120
100
80
Other
60
Universities
Big Pharma
40
Big Bio
20
0
4
9
14
19
24
29
Mean Distance From Other Organizations (Miles)
34