community ecology for it innovation...ping wang and jia sun science of science and innovation policy...

Ping Wang and Jia Sun Science of Science and Innovation Policy Principal Investigators' Workshop

September 20-21, 2012 Washington, DC

Community Ecology for IT Innovation

STICK: Science & Technology Innovation Concept Knowledge-base

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SOA

Cloud Computing

BPO

Semantic Web

Web 2.0 RFID

OSS

Business Intelligence

Mashup

Ajax

Social Media

DRM

Ultramobile Devices

Distributed Encryption

Chatbots

Thin Provisioning

CRM

VoIP

SaaS

Big Data

Application Quality Dashboards

Identity Management

SCM

Why do some innovations become highly popular, while others do not?

Varying Popularity, Varying Impacts

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BPR

ERP

KM

Data Warehouse

Groupware

CRM

ASP

E-Commerce

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1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

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BPR ERP KM Data Warehouse

Groupware CRM ASP E-CommerceWang 2010

Cloud Computing

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A model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction

Mell and Grance 2011, U.S. NIST Sam Johnston, Wikipedia

Innovation Community for CC

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Platform Provider

App/Service Provider

Adopter

Public Investor

Private Investor

Researcher

Analyst

Consultant

Innovation Community Ecology Legitimacy of innovation determines the

vitality of the innovation community. H1: Higher legitimacy higher

organizational entry rate Amount of resource is finite. Crowding causes competition for resource. H2: Higher competition lower

organizational entry rate

6 Hannan and Freeman 1977; Hannan et al. 1995

Innovation Community Structure

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Scale-free network has a few highly connected nodes. Scale-free networks are efficient in diffusing information,

rumors, and viruses. H3: Higher scale-free community higher organizational

entry rate

Random Scale-Free

Barabási 2003

Data Collection and Processing News articles about CC (2007-2011) Identified organizations with Stanford NER Cleaned results with CrowdFlower

Network of co-occurring organizations Visualized networks with NodeXL

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Cloud Computing Community in 2007 9

Data Analysis DV: Organizational Entry Rate IV-Legitimacy: Density IV-Competition: Density2 IV-Scale-freeness Control:

Prior entry rate Prior entry rate2 Year dummies

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Nov Ja

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2007 2008 2009 2010 2011

Article Count

Entry Rate

Regression on Org. Entry Rate Legitimacy

increases entry rate.

Competition hinders entry.

Scale-freeness positively affects entry rate.

Model explains ~73% variance.

Coef. S. E.

Density .198* .077

Density2 -.104* .036

Scale-free 191.351* 96.131

Prior entry -.160 .302

Prior entry2 3.362 2.961

Year 2008 15.302 12.596

Year 2009 6.737 17.459

Year 2010 2.292 21.893

Year 2011 28.269 26.952

Multiple R2 .727

F (df) 11.86 (40)

13 * p<0.05 (one-tailed test)

Takeaways Community ecology

Innovation community consists of multiple industries and ecology theory is applicable to multi-industry community.

Computational discourse analysis Discourse analysis captures attention flowing

across industries and computational approach scales up analysis for research and practice.

New ground for science of innovation More innovation communities, data sources,

periods, network structural metrics… 14

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Thanks and Contact Information Thanks to National Science Foundation for grant SBE-0915645 Ping Wang University of Maryland 4105 Hornbake Bldg. South College Park, MD 20742-4325 [email protected] stick.ischool.umd.edu

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References Barabási, A.-L. 2003. Linked: How Everything Is Connected

to Everything Else and What It Means. New York: Plume. Hannan, M.T., Carroll, G.R., Dundon, E.A., and Torres, J.C.

1995. "Organizational Evolution in a Multinational Context: Entries of Automobile Manufacturers in Belgium, Britain, France, Germany, and Italy," American Sociological Review (60:4), p.. 509-528.

Hannan, M.T., and Freeman, J. 1977. "The Population Ecology of Organizations," American Journal of Sociology (82:5), pp. 929-964.

Mell, P., and Grance, T. 2011. "The NIST Definition of Cloud Computing," September, National Institute of Standards and Technology, Gaithersburg, MD, pp. 1-7.

Wang, P. 2010. "Chasing the Hottest IT: Effects of Information Technology Fashion on Organizations," MIS Quarterly (34:1), pp. 63-85.

Production of Innovations

Hage & Hollingsworth 2000

Government Investors

Universities

Vendors

Venture Capitals

Government Labs

Designers Regulators

Ad Agencies


Basic Research Applied Research Product Development Manufacturing Marketing

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Use of Innovations

Swanson & Ramiller 2004

User Organizations

Universities

Media

Market Researchers

Consultants

Financiers Distributors

General Public

Use of Innovations

Comprehension Adoption Implementation Assimilation Abandonment

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Innovation Community


Universities

Vendors

Venture Capitals

Government Labs


Ad Agencies



User Organizations

Universities

Media

Market Researchers

Consultants


General Public

Use of Innovations


Supply

Demand Community for Innovation A

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Innovation Ecosystem


Universities

Vendors

Venture Capitals

Government Labs


Ad Agencies



User Organizations

Universities

Media

Market Researchers

Consultants


General Public

Use of Innovations


Supply

Demand Community for Innovation A

Community for Innovation B

Community for Innovation C

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community ecology for it innovation...ping wang and jia sun science of science and innovation policy...

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