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Record W148005812

Euro-Med as a market-driven regionalisation: measuring the role of tourism transnational companies in integrating European and North African markets.

2014· article· en· W148005812 on OpenAlexaboutno aff
Maxime Weigert

Bibliographic record

VenueJournal of tourism · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsRegionalisationTourismGlobalizationRegional integrationEuropean unionInternational tradeEconomic integrationGeographyEconomyEconomic geographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Introduction Since the beginning of the 1990s, the number of regional trade agreements (RTA) has dramatically increased, jumping from 27 in 1990 to more than 400 up to 2010 (Beckouche, 2011). Even if the majority of these agreements are bilateral ones, and as a result, the global mapping of RTAs is still a spaghetti ball, great regions have been emerging through institutionalized association (EU, ASEAN, MERCOSUR, ECOWAS, etc.). Most of the latter associate countries whose levels of development are comparable. However, in parallel of this phenomenon, a new type of regional economic cooperation appeared with the North America Free Trade Agreement (NAFTA), signed by Mexico, Canada and the United States in 1992. NAFTA was the first North-South regional agreement, i.e. the first which implied unequally developed economies. A few years after, the Euro-Med agreement of the Barcelona Process (1995) and then the ASEAN+3 initiative (1997) consolidated the hemispheric cooperation between industrialized countries and their southern neighbours, according to a core-periphery pattern. These processes take part into a broader manifestation of of the globalization (Beckouche, 2008; 2011). In fact, the evolutions of global economic trends reveal that international trade keeps turning regional: in 2011, the part of intra-regional trade was at 48% in the Americas, 55% in Asia-Oceania and 72% in Europe-CIS (Uzal, 2014). Tourism is also a highly regionalized activity. In the Southern Mediterranean countries for instance (from Turkey to Morocco), around 90% of inbound arrivals were coming from European Union or other southern Mediterranean countries in 2009 according to UNWTO (2011). The part of tourism in regionalisation has been highlighted by many authors (Shaw & Williams, 1998; Teo, 2001; Cochrane, 2008). Surprisingly, although they played a critical role in establishing the broad structures of international tourism, the role of tourism TNCs in regionalisation is an issue which has been seldom explored by economic geography (Weigert, 2013). Yet it has been the case for manufacturing transnational companies (TNCs). Many authors have taken an interest in the part transnational systems of production in regional integration, emphasizing the fact that North-South regionalisation proceeds fore and foremost, even if not exclusively, from a market-driven integration governed by private actors, e. g. by lead firms involved in global production networks (Ohmae, 1996; Langhammer, 1996; Bevan & Estrin, 2000; Barba Navaretti & Venables, 2004; Capling & Nossal, 2008; Gereffi & Mayer, 2010). Whereas regionalism studies have been focusing on the institutional governance of regionalisation (Hameiri & Jayasuriya, 2011), viewing regulation as a government-driven process and regional integration as a result of international public cooperation (Haufler, 2003), this paper offers an insight into alternative forms of regional integration governance, in particular at a North-South scale. The main purpose of this manuscript is to present an original methodology for measuring the key-role tourism TNCs play in the market-driven dynamics of unequally developed economies. By considering TNCs as global production systems, it is possible to focus the analytical methodology on inter-firm linkages between the home companies and the indigenous firms established in the southern markets. After specifying the self-regulation process through which tourism TNCs manage these linkages, the approach consists in exploring whether regulatory transfers occurring throughout the North-South network of production entail a market-driven regulation convergence. In a second phase, the paper will set out the spatial outcomes of tourism TNCs-driven integration in the specific case of Tunisia and Morocco, where European TNCs act as major players of the tourism regionalisation. Theoretical framework: TNCs and North-South integration Regional integration is a product of many forces and drivers (Mattli, 1999), but one of the primary incentives has to do with economics, in particular in the North-South schemes (Beckouche, 2008). …

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.197
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2014
Admission routes1
Has abstractyes

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