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This Author published in this journals
All Journal Journal of E-business and Management Science International Journal of Computer Science and Humanitarian AI
Maria Loura Christhia
Bina Nusantara University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Social Sciences

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Optimizing Fashion Retail Shelf Management for Enhanced Consumer Experience: A Literature Review Maria Loura Christhia
Journal of E-business and Management Science Vol. 1 No. 1 (2023): Juni 2023
Publisher : PT. BERBAGI TEKNOLOGI SEMESTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61098/jems.v1i1.41

Abstract

This study aims to optimize shelf display management in the fashion retail industry to cater to the evolving needs and desires of consumers for specific products. With the ever-expanding range of fashion items available in retail stores, the limited space on display shelves poses a significant challenge. Additionally, trendy, and high-demand fashion products often experience quick sell-outs, necessitating frequent restocking. Effective management of shelf displays is pivotal in enhancing consumer satisfaction and stimulating impulse purchases by maximizing product visibility and exposure. In the realm of fashion retail, shelf display management can be broadly categorized into macro and micro levels, encompassing strategic overall layout and precise product allocation within specific fashion categories. However, these approaches heavily rely on the availability of demand and transaction data, which can be challenging for small and medium-sized fashion enterprises with limited data resources. This literature review underscores the research opportunities for optimizing shelf display management, particularly in the context of fashion retail businesses facing data limitations. It recognizes that through thoughtful facility layout design, coupled with suitable adjustments and modifications, the challenges associated with shelf displays in fashion retail stores can be effectively addressed.
A Literature Review on AI and DSS for Resilient and Sustainable Humanitarian Logistics Maria Loura Christhia; Olivia Oktariska Timbayo; Ahmad Ardi Wahidurrijal; Abimanyu Bagarela Anjaya Putra
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 1 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i1.13028

Abstract

Disaster response is a critical component of disaster management, requiring effective strategies to reduce exposure and vulnerability to hazards. Rising global temperatures and extreme weather events have intensified the need for adaptive disaster relief systems. Humanitarian logistics, a vital subset of the supply chain, plays a central role in disaster preparedness, response, and recovery phases but often faces challenges such as resource constraints, inefficient communication, and  unpredictable  crises.  This  study  employs a systematic literature review (SLR) using the PRISMA methodology to explore the application of Artificial Intelligence (AI) and Decision Support Systems (DSS) in humanitarian logistics from 2019 to 2024. SCOPUS served as the primary database, identifying 1,171 documents, with 52 studies selected for in-depth analysis. These studies highlight the potential of AI techniques, including machine learning and clustering algorithms, and DSS implementations for resource allocation, stakeholder coordination, and real-time decision- making. Findings demonstrate that integrating AI and DSS can optimize emergency vehicle routing, improve relief distribution, and enhance stakeholder collaboration. Advanced technologies such as Radio Frequency Identification (RFID), the Internet of Things (IoT), and Digital Twins improve logistics efficiency and scalability. Despite these advancements, challenges like data integration and algorithmic reliability persist. The study recommends prioritizing transparent systems, hybrid simulations, and addressing algorithmic constraints to advance disaster management practices.
Co-Authors Abimanyu Bagarela Anjaya Putra Ahmad Ardi Wahidurrijal Olivia Oktariska Timbayo