International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 3
May-June 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Predictive Analytics in Retail Pharmacy: QR Code Implementation on Purchase Intentions Using Random Forest

Author(s) Ms. Catrina Mae Tulinao, Dr. Nelson Bool
Country Philippines
Abstract In this study, we explore the efficacy of a Random Forest model in predicting customer repurchase intentions in a retail pharmacy setting that has adopted QR code technology. The model achieved a training R² of 0.6964 and a testing R² of 0.4558, indicating that while it captures a substantial proportion of the variation in the training data, its performance on independent data calls for cautious interpretation. Notably, feature importance analysis highlighted that store attributes and service quality are critical determinants of repurchase behaviour, explaining 32.91% and 29.86% of the variance, respectively. Additional factors, such as the physical store environment and waiting time, also played significant roles. These findings suggest that both tangible store features and digital interventions contribute to customer loyalty. The integration of rigorous model validation techniques, including cross-validation and hyperparameter tuning, reinforces the model’s potential as a robust predictive tool. This work provides meaningful insights for retail pharmacies aiming to optimize customer engagement through a blended approach of digital innovation and traditional service excellence.
Keywords Retail pharmacy, QR code, Random Forest, repurchase intention, feature importance, predictive modelling, customer behavior, service quality, store attributes, digital integration
Field Business Administration
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-26
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.40544
Short DOI https://doi.org/g9gvd5
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com