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Record W3046094034 · doi:10.1108/ijqrm-12-2019-0386

Integrated management systems as a driver of sustainability performance: exploring evidence from multiple-case studies

2020· article· en· W3046094034 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Quality & Reliability Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Management Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSustainabilityOriginalityBusinessPortfolioTriple bottom lineProcess managementKnowledge managementCorporate sustainabilityCorporate social responsibilitySocial sustainabilityComputer sciencePublic relationsQualitative research

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to analyze the impact of integrated management systems (IMSs) on sustainability (based on the triple bottom line (TBL) concept). To accomplish this objective, this paper seeks to answer the following research questions: How can IMS impact organizational sustainability performance? And, how the key challenges of IMS can influence companies in practice? Design/methodology/approach A case-based approach is used based on the following four cases from different sectors: an electric power distributor; an environmental consulting firm; a public transport firm; and a firm with a broad portfolio of equipment, products and provisions for industrial services in different markets. Findings The results show that the integration of management systems was driven by the companies' strategies toward sustainability. The stakeholders' perception is that a firm's image as a sustainable company also enhances environmental and social performance. The economic performance was not emphasized. Companies noted that the main challenge was motivating and engaging human resources. Originality/value This paper shows that sustainability was not a motivation for implementing an IMS. But, implementing an IMS was a driver of sustainability performance. Also, the relationship between IMS and organizational performance can be presented based on TBL perspectives, and implementing an IMS can be challenging in practice.

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.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.142
GPT teacher head0.346
Teacher spread0.204 · 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