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Record W4399591976 · doi:10.58532/v3bhma7p1ch8

FOREIGN DIRECT INVESTMENT AND FUTURE OF INDIAN ECONOMY

2023· book-chapter· en· W4399591976 on OpenAlexaboutno aff
Ms. Rishita Das, Pawan Kumar Sharma

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentDiversification (marketing strategy)BusinessCurrencyInternational economicsCompetition (biology)International tradeEconomicsMonetary economics

Abstract

fetched live from OpenAlex

Foreign direct investment (FDI) is the key source for the inflow of foreign currencies in India. After the adoption of LPG policies with opening the door of Indian economy for foreign trade by the year 1991, India is growing year by year in this segment. FDI provides opportunities to domestic companies for the growth of their business and product diversification. Domestic companies can get advantages in terms of technological advancement. Job creation as well as global integration is the core outcomes because of foreign direct investment. Present chapter will regard as to show the relationship between foreign direct investment (FDI) and the development of Indian economy. However government’s role is significant for the development of FDI in the country. Few evidences in form of FDI flows in Indian economy will be the part of present chapter. Few sectors such as Education, research & development (111.1%), Computer services (51.4%), Transport (41.7%), Electricity and Other Energy Generation, Distribution & Transmission (26.9%), Manufacturing (17.7%) and Retail & Wholesale Trade (8.2%) are showing positive results. Few countries as Cyprus (333.3%), UAE (277.8%), US (93.5%), Luxembourg (66.7%), Canada (33.3%) and UK (21.4%) are full with FDI for Indian economy. Foreign direct investment (FDI) is full with lot of benefits for India in form of jobs creation, global market reach, investment opportunities, business diversification, economic growth and increase in the foreign currency reserve. However FDI is problematic because FDI increase foreign intervention, increase competition for domestic companies and not in the favor of poor people. Besides all Foreign direct investment (FDI) is the need of present era in the globalised business activities. Indian economy is the fastest developing economy can avail more opportunities for the pace of growth & development with FDI.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.025
GPT teacher head0.200
Teacher spread0.175 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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