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A Balanced Scorecard Framework for Measuring Sustainability Performance of Business Organizations

2019· book-chapter· en· W2986406344 on OpenAlexaff
Varun Arora

Bibliographic record

VenueAdvances in logistics, operations, and management science book series · 2019
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsBalanced scorecardSustainabilityCorporate social responsibilityBusinessProcess managementStrategy mapProcess (computing)Business processSustainability organizationsField (mathematics)Computer scienceMarketingPublic relationsWork in processPolitical scienceMathematics

Abstract

fetched live from OpenAlex

Sustainability is about meeting the needs of today without compromising the needs of future generations. It involves focus on three main dimensions, economic, environmental, and social, for achieving overall performance. Majority of the companies are adopting sustainability for business growth and boosting their corporate image for long term competitiveness, thereby receiving financial benefits as well. Sustainability is a concept that has come into picture a few years back and presently making a big mark in every field. A balanced scorecard framework is proposed for measuring sustainability performance of business organizations. Four main dimensions are considered, namely organization, process, core, and learning. Each of these dimensions comprises of various indicators obtained from global reporting initiative (GRI) and corporate social responsibility reports. The application of the sustainability scorecard is performed via multi criteria decision making technique called analytical network process (ANP). A numerical study is provided.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.006
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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2019
Admission routes1
Has abstractyes

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