University of Sussex
Browse
RA9WP 2010 JIM From Blind Spots to Hotspots.pdf (293.44 kB)

From blind spots to hotspots: How knowledge services clusters develop and attract foreign investment

Download (293.44 kB)
journal contribution
posted on 2023-06-09, 19:05 authored by Stephan ManningStephan Manning, Joan E Ricart, Maria Soledad Rosatti Rique, Arie Y Lewin
This paper explores local and global dynamics underlying the development of knowledge services clusters, which we define as new geographic concentrations of technical talent and service providers offering upstream technical and knowledge-intensive business services to regional and global clients. Taking a co-evolutionary perspective on the development of knowledge services clusters in Latin America, based on data from the Offshoring Research Network (ORN), we find that cluster growth results from intersecting trajectories: the emergence of local talent pools and capabilities initially serving local and regional demand; broadening global search for talent and expertise by multinational corporations; and internationalization strategies of service providers competing to serve global clients. Findings suggest that increasing commoditization of knowledge services opens up windows of opportunity for new clusters, but also involves challenges for sustainable growth. Results may stimulate future research on global sourcing and cluster development.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Journal of International Management

ISSN

1075-4253

Publisher

Elsevier

Issue

4

Volume

16

Page range

369-382

Department affiliated with

  • Business and Management Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2019-09-23

First Open Access (FOA) Date

2019-09-23

First Compliant Deposit (FCD) Date

2019-09-23

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC