Authors:
Stefan Kambiz Behfar
1
;
Tina Afshar
2
and
Parmiss Afshar
3
Affiliations:
1
HEC Montreal, Canada
;
2
Parsian Bank, Iran, Islamic Republic of
;
3
Transportation and Traffic Organization, Iran, Islamic Republic of
Keyword(s):
SME, Diffusion of Innovation, Adoption, Adaptation, Cluster Network Model.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Software Engineering
;
Symbolic Systems
Abstract:
Since Rogers (1995) first gave a typology of innovation diffusion, there have been many studies on the role of networks in the topic of innovation diffusion and adoption. Bradley (1995) defined technology diffusion as the spread of a new technology from one SME to another; whereas DiMaggio and Powell (1991) emphasized that under conditions of uncertainty, inter-organizational diffusion of innovation occurs through imitation (adaptation). Other authors have investigated rate of innovation where importance was given to the number of firm linkages and geographical proximity (Florida 1995, Van Oort 2004). Although the role of ties has been studied with regard to innovation diffusion and knowledge sharing, to the best of our knowledge, there has been no published research concerning efficient innovation diffusion and adoption within SME cluster networks, where efficient innovation diffusion with cluster is defined when most SMEs within each cluster could adopt innovation. Here, we presen
t a cluster network model for inter-SME diffusion of innovation where SMEs represent nodes, and innovation adoption and adaptation between any two SMEs represent ties. In such a model, we differentiate between SMEs as either sources or beneficiaries of innovation, and discuss creation of ties among those SMEs and among cluster of SMEs. This study presents a conceptual piece, where we provide three propositions a) The network model contains both source and beneficiary of innovation, where the beneficiary adopts an innovation from source, or adapts to the innovation of another beneficiary, b) The more efficient diffusion of innovation from one SME cluster to another is when two clusters interconnect strongly rather than loosely, c) The rate of innovation adoption among SMEs depends on their network dependency.
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