| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | August 26, 2011 |
| Latest Amendment Date: | August 26, 2011 |
| Award Number: | 1121935 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Rajiv Ramnath
OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2011 |
| End Date: | August 31, 2015 (Estimated) |
| Total Intended Award Amount: | $182,062.00 |
| Total Awarded Amount to Date: | $182,062.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
10900 EUCLID AVE CLEVELAND OH US 44106-4901 (216)368-4510 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
10900 EUCLID AVE CLEVELAND OH US 44106-4901 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
INNOVATION & ORG SCIENCES(IOS), VIRTUAL ORGANIZATIONS, SOCIAL-COMPUTATIONAL SYSTEMS |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Economic competitiveness relies upon innovation and digitized tools, services and data representation. These innovations are required for organizations to remain effective. Designers and design managers guide the evolution of digitally enabled design capabilities by integrating different types of digital process capabilities and resources. Such capabilities can also help optimize complex systems (e.g., smart grid, pervasive healthcare). Building on organizational and evolutionary theory, this project studies changes in organizational processes as they incorporate innovative virtual elements. It applies a process modeling framework to explore underlying mechanisms that generate patterns of change, and uses computational tools in conjunction with theories of evolutionary genetics to analyze longitudinal changes in organizational processes for integrating virtualized innovations. Generative structural elements of design processes (e.g., genotypes) give birth to surface-level design routines and variations (e.g., phenotypes) over time. Processes are represented as sequences akin to biological genes and their translated protein products. while combinations of elements akin to DNA base pairs and their corresponding amino acids capture essential traits of design activity. This new vocabulary helps us delineate structurally the fundamental design task elements and their variation across design task instances.
The study advances theoretical understanding of how digital capabilities alter organizational processes. It shows how mutations emerge and how processes change over time. It identifies strategies for embedding digital capabilities into processes, and explores the impact of complexity. It advances instrumentation, methodology and analytical techniques by describing digitally-enabled processes and performing comparative, hierarchical, structural-analytical analyses of event-sequence-based process data. It provides longitudinal data on the micro- and meso-level changes in design processes from systematic studies of design for cars, chips and buildings. Genetics research is used to evaluate design in light of evolutionary models and agent-based simulations and to identify patterns of integration of digital capabilities into design processes over time.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Economic competitiveness relies upon innovation and digitized tools, related services and data representation. These innovations are vital for organizations to remain competitive. Designers and design managers thus drive the evolution of digitally enabled design capabilities by integrating different types of digitally supported process capabilities and resources. Such capabilities can also help optimize complex systems (e.g., smart grid, pervasive healthcare).
Building on organizational and evolutionary theory, this project studies changes in organizational processes as they incorporate innovative virtual elements. It applies a novel process modeling framework to explore underlying mechanisms that generate patterns of change, and uses computational tools in conjunction with theories of evolutionary genetics to analyze longitudinal changes in organizational processes that integrate virtualized innovations. Generative structural elements of design processes (e.g., genotypes) give birth to surface-level design routines and variations (e.g., phenotypes) over time. Processes are represented as sequences akin to biological genes and their translated protein products while combinations of elements akin to DNA base pairs and their corresponding amino acids capture essential traits of design activity. This new vocabulary helps us delineate structurally the fundamental design task elements and their variation across design tasks. The study advances theoretical understanding of how digital capabilities alter organizational processes. It shows how process mutations emerge and how processes change over time. It identifies strategies for embedding digital capabilities into processes, and explores the impact of complexity. It advances instrumentation, methodology and analytical techniques by describing digitally enabled processes and performing comparative, hierarchical, structural-analytical analyses of event-sequence-based process data. It provides longitudinal data on the micro- and meso-level changes in design processes from systematic studies of design for cars, chips and buildings. Genetics research is used to evaluate designs in light of evolutionary models and agent-based simulations and to identify patterns of integration of digital capabilities into design processes over time.
Last Modified: 09/09/2015
Modified by: Kalle J Lyytinen
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