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Record W2902986360 · doi:10.5539/ibr.v11n12p89

Outcomes of Sustainable Practices: A Triple Bottom Line Approach to Evaluating Sustainable Performance of Manufacturing Firms in a Developing Nation in South Asia

2018· article· en· W2902986360 on OpenAlexvenueno aff
S. Sapukotanage, B. N. F. Warnakulasuriya, S. T. W. S. Yapa

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsTriple bottom lineBusinessSustainable developmentContext (archaeology)Sustainable growth rateSustainabilityDeveloping countryEnvironmental economicsEconomic growthEconomicsPolitical scienceFinanceGeography

Abstract

fetched live from OpenAlex

Maintaining sustainable operations has become a major responsibility of practitioners. Sustainable practices are executed to ensure sustainable performance. Many studies conducted to examine the outcomes of sustainable practices have focused either on the economic outcomes, social outcomes or environmental outcomes of such operations disregarding the Triple Bottom Line Approach to evaluating sustainable performance. Among them the majority have focused on environmental outcomes. Less focus is placed on developing countries or countries in South Asia. Against this background this paper aims to examine the outcomes of sustainable practices towards sustainable performance of manufacturing firms in a developing nation in South Asia. A study was conducted among 154 apparel manufacturing and exporting firms of Sri Lanka in relation to their sustainable practices and sustainable performance as members of supply chains. The sustainable practices were studied in relation to orientation, collaboration, continuity, risk management and pro-activity while sustainable performance was analyzed along economic performance, social performance and environmental performance of these firms. The findings were analyzed using Variance Based Structural Equation Modelling (Partial Least Squares) and it revealed that sustainable practices lead to sustainable performance even in the context of a developing nation in South Asia, highlighting the importance of the execution of sustainable practices irrespective of the level of development of a nation.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.157
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.133
GPT teacher head0.396
Teacher spread0.264 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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