دانلود مقاله ISI انگلیسی شماره 12359
ترجمه فارسی عنوان مقاله

از نقاط کور تا نقاط مهم: چگونه خوشه های خدمات دانش، سرمایه گذاری خارجی را توسعه و جذب می کنند

عنوان انگلیسی
From blind spots to hotspots: How knowledge services clusters develop and attract foreign investment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
12359 2010 24 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of International Management, , Volume 16, Issue 4, December 2010, Pages 369-382

ترجمه کلمات کلیدی
خدمات دانش -      توسعه خوشه -      اقتصادهای در حال ظهور -      سپارش جهانی -      انتخاب محل سکونت -      قابلیت های سرویس -      کالایی -
کلمات کلیدی انگلیسی
Knowledge services, Cluster development, Emerging economies, Global sourcing, Location choices, Service capabilities, Commoditization,
پیش نمایش مقاله
پیش نمایش مقاله  از نقاط کور تا نقاط مهم:  چگونه خوشه های  خدمات دانش، سرمایه گذاری خارجی را توسعه و جذب می کنند

چکیده انگلیسی

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.

مقدمه انگلیسی

In recent years, sourcing knowledge-intensive business services, such as software development, product design, R&D and analytical services, from emerging economies has become an established business practice (UNCTAD, 2005, Kenney et al., 2009 and Manning et al., 2008). Knowledge services involve symbolic–analytical work, are typically more complex, and require higher-skilled personnel to be performed than administrative business services, e.g. payroll processing, and call centers. Multinational corporations (MNCs) source knowledge services from abroad mainly to tap into growing pools of qualified, yet often cheaper personnel and specialized expertise outside their home countries (e.g. Doh, 2005 and Lewin et al., 2009). They do so either by setting up wholly owned subsidiaries (captive delivery models) or by contracting with specialized service providers (outsourcing) (Couto et al., 2008). This trend has co-evolved with the development of knowledge services clusters—new geographic concentrations of technical science and engineering (S&E) talent and service providers offering upstream technical and knowledge-intensive business services, e.g. engineering, R&D, design, software and analytical services, for regional and global clients (see also Manning et al., 2008). A number of recent studies have examined the emergence of service capabilities and clusters particularly in India (e.g. Bresnahan et al., 2001, Dossani and Kenney, 2007, Athreye, 2005 and Ethiraj et al., 2005). China has also been recognized as an emerging destination for sourcing product development services (Altenburg et al., 2007). However, recent studies suggest that Western MNCs, facing growing competition for talent, have increasingly broadened their global search for talent and expertise (e.g. Heijmen et al., 2009). At the same time, as knowledge services have become more commoditized, new second-tier knowledge services clusters, e.g. in North Africa and Latin America, have developed and begun to attract investment by Western client companies and international service providers (Couto et al., 2008). Despite the increasing number of studies investigating sourcing location choices (e.g. Doh et al., 2009) and the emergence of service capabilities in emerging economies (e.g. Athreye, 2005), we lack an understanding of the dynamics underlying the more recent development of knowledge services clusters across the globe. In this study, we take a co-evolutionary perspective on the development of knowledge services clusters, based on the empirical example of Latin America. Using both quantitative and qualitative data of client investment decisions and provider capabilities, collected by the Offshoring Research Network (ORN), we explore inductively how Latin America has increasingly attracted foreign investment in a changing global sourcing context. Unlike previous studies which primarily focus on local factors contributing to cluster development, e.g. government policies, specialization of suppliers etc., (e.g. Dossani and Kenney, 2007 and Athreye, 2005), we look at the intersection of global and local dynamics promoting cluster growth. Also, unlike previous studies, we show how increasing commoditization of services as well as the internationalization of service providers is currently changing the landscape of knowledge services sourcing. Based on our empirical findings we construct a dynamic model of cluster growth in the global sourcing context to inform future research. In particular we seek to contribute to the emerging literature on knowledge services clusters and capabilities on the one hand (e.g. Athreye, 2005 and Ethiraj et al., 2005), and sourcing strategies and location choices on the other hand (Doh, 2005 and Doh et al., 2009). The rest of the paper is organized as follows: Section 2 presents the rationale for a co-evolutionary perspective to study the development of knowledge services clusters. Section 3 presents the data for Latin America. We combine some quantitative and qualitative data as a way to further develop our co-evolutionary perspective. Section 4 presents the discussion and develops from the data a dynamic model of cluster growth that is fully coherent with the co-evolutionary perspective. We end with some policy as well as managerial implications, and with follow-up ideas for future research.