The Effects of Physical Location on Communication Patterns (Continued)
May 5, 2007
Some Obvious Points
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Office Configuration to Vary Privacy and Accessibility.
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Floor to
CeilingPanels
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Combining Physical & OrganizationalBarriers & Bonds
The Effects and Organizational Separation as Measured in One Organization
DIFFERENT DEPARTMENTSAND PROJECTS
SAMEDEPARTMENT
DIFFERENT PROJECTS
SAME PROJECT DIFFERENT
DEPARTMENTS
SAMEDEPARTMENT AND PROJECT
SAME WING 0.16 0.69 0.71 0.95
SAME FLOORDIFFERENT
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0.05 0.53 0.80 ___
SAME BUILDING DIFFERENT
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SAME SITE DIFFERENT BUILDINGS
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DIFFERENT SITES
0.002 0.15 0.23 0.38
Two Departments in Separate Locations
LOCATION I LOCATION II
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The Effect of Transferring Staff Between Locations
LOCATION I LOCATION II
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Moving Staff Between Sites to Increase Interdepartmental Communication
(Examples from Laboratories ‘H’ & ‘I’)
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Proportional Increase in Interdepartmental Communication
Prop
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Proportion Moved
10%
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Lab 'I'Lab 'H'
Moving Staff Between Buildings to Increase Interdepartmental Communication(An Example from Laboratory ‘H’)
0.7
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0.8
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Proportional Increase in InterdepartmentalCommunication
Prop
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30%
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Proportion Moved
Moving Staff Between Floors of a Building to Increase Interdepartmental Communication
(An Example from Laboratory ‘I’)
0.5
0.6
0.7
0.8
0.9
1
1 2 3 4 5
Proportional Increase in InterdepartmentalCommunication
Prop
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Com
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Proportion Moved
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 inverselyproportional to the amount of communication reported.
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Figure by MIT OCW.
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A Super Cluster?
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Inside The Super Cluster
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Where are the Universities?
Universities
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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’
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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?
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Mean Distance From Other Organizations (Miles)
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Where are the Universities?
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Where is Big Pharma?
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