Taking the Long View of Cluster Ecosystem Model Case study: Iranian Native Search Engine

Document Type : Original Research Manuscripts

Authors

1 Assistant Professor, Department of Technology and Innovation Policy, National Research Institute for Science Policy, Tehran, Iran

2 Faculty Member ,Information Technology Department, Research Institute for Information and Communication Technology, Tehran, Iran

Abstract
Innovation and economic growth is mainly formed by a unique combination of the companies that are interconnected in the field of knowledge and process. Such connections can be based on different goals among the service provider companies while two common methods for this objective include the cluster and ecosystem. The main objective of this article is to develop the cluster ecosystem of Iranian native search engine. In the ecosystem, relationship between the actors are formed based on the function-oriented complementary relationship of cluster of Iranian native search engine. This article aims at understanding the relating concepts of high-tech clusters and business ecosystems. Thus, while studying the existing literature, identified the different functions of native search engine clusters and different types of the actors and stakeholders of ecosystem by related experts. Then considering the role of each actor in the general functions of the native search engine, we tried to identify the relationships and interactions among those actors. Finally, the cluster ecosystem development model for the Iranian native search engine was designed based on the value network among the actors of Iranian native search engine. The findings of this research included: 1. identifying the ecosystem actors of native search engine, 2. developing the cluster of search engine functions, 3. designing the value network of the mentioned ecosystem.
Originality/ value: the proposed model, makes it possible for the actors to begin the interaction and value flow based on their roles in the cluster.

Keywords

Subjects

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  • Receive Date 25 October 2022
  • Revise Date 31 December 2022
  • Accept Date 26 January 2023