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Record W2151230530 · doi:10.5267/j.msl.2012.09.022

A study to measure the impact of customer perception, quality, environment concern and satisfaction on green customer loyalty

2012· article· en· W2151230530 on OpenAlexvenueno aff
Hamid Reza Saeednia, Saeeid Khodaei Valahzaghard

Bibliographic record

VenueManagement Science Letters · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsCustomer satisfactionLoyalty business modelMeasure (data warehouse)BusinessLoyaltyPerceptionMarketingQuality (philosophy)Customer delightService qualityPsychologyComputer scienceService (business)Data mining

Abstract

fetched live from OpenAlex

Green product management plays an important role in today's economy and people are increasing becoming more interested in green products. In this paper, we present an empirical study to measure the impact of customer perception, quality, environment concern and satisfaction on green customer loyalty. The study proposes two hypotheses, where the first hypothesis studies whether the quality of green product has direct impact on customer satisfaction and the second hypothesis examines whether quality of green product has direct impact on customer loyalty. The population of this paper includes all people who use paperbased drinking glass, napkin and packaging products and live in city of Tehran, Iran. Since not all people are involved in all parts of the city in such product, we have decided to select only those who are involved in using these kinds of products including hospitals, universities, etc. The sampling technique has distributed 300 questionnaires and gathered 283 good quality ones for analysis. The questionnaire consists of 19 questions in five different perspectives. The proposed study uses sequential equation modeling and the results have confirmed both hypotheses.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.011
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.030
GPT teacher head0.288
Teacher spread0.258 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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