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International Services: The Interface Between Service Characteristics, Policy, and Institutions

2021· book-chapter· en· W3129477564 on OpenAlexaff
Kristin Brandl, Peter D. Ørberg Jensen, Andrew Jones, Patrik Ström

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDirectiveBusinessService (business)Variety (cybernetics)RatificationService designEuropean unionService delivery frameworkKnowledge managementPublic relationsMarketingPolitical scienceInternational tradeComputer sciencePolitics

Abstract

fetched live from OpenAlex

Abstract The implemented European Union Services Directive aimed at creating a unified European market for trade in services. However, the implementation of the institutions was not fully successful as to the characteristics of international services caused challenges in the ratification of the Directive. Research on international services is facing similar challenges based on the fragmented, inconclusive, and at times even contradictory findings of international services literature with regard to service characteristics. Thus, each academic field of international business, economic geography, and service management has tried to identify international service characteristics, but no unified characterization is found. The challenges in defining the different types of services, difference in the levels of analysis, and various impacts of policies and institutional environments on the service, cause these differences. The authors see the need for a unified framework that combines the different literatures and considers the policy implications. The authors develop a framework consisting of four components of international service characteristics, that is, the connectivity of service actors to the environment, the configuration of service activities within organizational set-ups, the dyadic collaborative interaction between service actors, and the created value by the services. The authors specifically consider policy and institutions as well as a vast variety of literature streams to support the arguments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.005
Scholarly communication0.0080.005
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.051
GPT teacher head0.294
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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