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Record W4245388998 · doi:10.17722/ijme.v8i2.886

Perspective of Developer, Buyer, Financier and Equity Participants in Real Estate Project Development Process in India: An important constituent of Construction Industry

2017· article· en· W4245388998 on OpenAlexvenueno aff
Alok Kumar Singh

Bibliographic record

VenueInternational Journal of Management Excellence · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsReal estateReal estate developmentCorporate Real EstateBusinessReal estate investment trustCapitalization ratePortfolioFinanceIncome approachCost approachMarketing

Abstract

fetched live from OpenAlex

The real estate project development is an important constituent of construction industry. The other important constituent of construction industry is infrastructure development. The construction industry drives and impacts many other industries and has a substantial multiplier effect on various sectors and hence on economic output as well as on employment scenarios. This article discusses multiplier effect of construction industry on few of the important economic indicators and further focuses on real estate project development process. The real estate project development process starts from land acquisition to sales and marketing. The internal stakeholders in real estate project development process are real estate developers, real estate buyers and the real estate financers. The paper discusses alternatives for real estate developers, the opportunistic schemes for real estate buyers, and the role of portfolio of financing agencies as well as the role of multitudes of equity participants. It also describes about the regulatory institutions active in real estate project development and promotion process. The real estate projects are developed by organized real estate project developer as well as by unorganized real estate project developers or local builders. This article contributes regarding the challenges and opportunities among the real estate buyers, real estate developers, portfolio of financial schemes offered by real estate financers and the opportunities for real estate equity participants.

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 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)0.003
metaresearch head score (Gemma)0.001
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 score0.216
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.145
GPT teacher head0.464
Teacher spread0.319 · 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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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