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AN AHP BASED EXPERT STUDY OF INTRINSIC PSYCHOLOGICAL DETERMINANTS OF APPAREL PURCHASES IN AN INDIAN METROPOLITAN CITY

2025· article· W7117694351 on OpenAlexaff
Bratin Maiti, Malini Majumdar, Protik Basu

Bibliographic record

VenueInternational Journal of Research -GRANTHAALAYAH · 2025
Typearticle
Language
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsHeritage College
Fundersnot available
KeywordsAnalytic hierarchy processConsistency (knowledge bases)ClothingPerceptionPersonalityRanking (information retrieval)Pairwise comparisonMetropolitan area

Abstract

fetched live from OpenAlex

In today’s competitive market, understanding the drivers of consumer purchase decisions is critical for the retailers. This study uses an expert based Analytic Hierarchy Process (AHP) to prioritize six intrinsic psychological factors namely motivation, attitude, perception, learning, personality and self-esteem believed to influence apparel purchase decisions in Kolkata’s organized retail sector. Three domain experts selected on the basis of their experience provided pairwise comparisons. Group judgments were aggregated using the geometric mean method. Individual and aggregated values of maximum eigenvalue (λ max), consistency index (CI) and consistency ratio (CR) were computed. All CR values were below 0.10, indicating acceptable consistency of expert judgments. Final AHP results revealed motivation (44.72%) as the most influential factor, followed by attitude (24.30%), perception (14.42%), self-esteem (7.43%), learning (7.05%), and personality (3.45%). Results of the study suggest marketers to concentrate on motivational stimuli, attitudinal interventions, perceptual cues and communication strategies to influence customers for purchase. However, small expert panel, lack of direct consumer feedback and confinement to one city are limitations of the study. Future studies with more experts and consumer feedback across different cities can validate the findings. Multi-criteria decision approach for pair wise comparison and ranking of internal factors adds to the literature in the area of consumer psychology. The study provides practical recommendation to the marketers to shape consumer perception and their purchase behaviour.

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)0.005
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
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
Bibliometrics0.0070.002
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0030.001
Research integrity0.0000.001
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 head0.137
GPT teacher head0.491
Teacher spread0.354 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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