Who hates your brand? An analysis of consumer brand hater typology DOI

Oula Bayarassou,

Imène Becheur, Pierre Valette‐Florence

et al.

Asia Pacific Journal of Marketing and Logistics, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 10, 2024

Purpose The purpose of this study is to develop a typology brand haters, depending on their coping processes the different stressful consumption situations, and associate these hate profiles with corresponding psychological traits. Design/methodology/approach paper uses mixed methodology composed two phases, qualitative quantitative one, conducted simultaneously. aim define clusters antecedents consequences better understand responses haters. This phase OMIE (Multi-Image Elicitation) tool. During phase, series multiple correspondence analyses (MCAs) allows characterizing mapping each segment haters according personality traits identified during phase. Findings Depending motives hate, we three distinct types First, rational are particularly sensitive brand’s deceptive nature, leading deep feelings disappointment efforts avoid brand. Next, hostile express an active form driven by unauthentic practices or ideological reasons (e.g. exploitation children), often focus revenge. Lastly, threatened experience both passive forms stemming from perceived physical mental threats that extend beyond individual complaints broader societal issues. In terms profiles, our findings suggest may exhibit extraverted sophisticated personalities. Hostile other hand, associated conscientious Finally, characterized as agreeable creative. Originality/value unique approach map hater Additionally, employed in research contributes its originality.

Language: Английский

ENHANCING FASHION FORECASTING ACCURACY THROUGH CONSUMER DATA ANALYTICS: INSIGHTS FROM CURRENT LITERATURE DOI Creative Commons

Md Rohul Amin,

Shakhauat Hossen Morshedul Islam Mridha Younus,

Shakhauat Hossen

et al.

Academic journal on business administration, innovation & sustainability., Journal Year: 2024, Volume and Issue: 4(2), P. 54 - 66

Published: June 12, 2024

The fashion industry is characterized by its fast-paced nature and constant evolution of consumer preferences, making accurate forecasting essential for brands to remain competitive. Traditional methods, which rely heavily on historical sales data expert intuition, are increasingly being complemented or replaced advanced analytics. This article explores the integration analytics into forecasting, drawing insights from recent literature. By examining methodologies such as machine learning, big analytics, AI, well utilizing diverse sources including social media, online shopping behaviors, mobile data, this study highlights significant improvements in trend prediction accuracy operational efficiency. Key findings indicate that data-driven approaches provide more precise real-time enabling better anticipate market demands optimize inventory management. discussion underscores transformative potential enhancing overall effectiveness forecasting.

Language: Английский

Citations

7
BIG DATA-DRIVEN DECISION MAKING IN PROJECT MANAGEMENT: A COMPARATIVE ANALYSIS DOI Creative Commons

Md Atiqur Rahaman,

Farhana Zaman Rozony,

Md Samiul Alam Mazumder

et al.

Academic journal on science, technology, engineering & mathematics education., Journal Year: 2024, Volume and Issue: 4(3), P. 44 - 62

Published: July 24, 2024

This study investigates the impact of big data-driven decision-making in construction project management through a qualitative comparative analysis. By conducting semi-structured interviews with managers, data analysts, and workers across various types projects, research identifies key themes related to benefits challenges integrating analytics. The findings highlight significant advantages such as enhanced operational efficiency, improved processes, cost reduction, budget management, timely delivery, quality control assurance. However, including integration complexities, privacy concerns, need for specialized skills, organizational resistance change are also revealed. underscores importance fostering culture strong leadership support maximize while emphasizing context-specific strategies tailored different types.

Language: Английский

Citations

5
A REVIEW OF IMPLEMENTING AI-POWERED DATA WAREHOUSE SOLUTIONS TO OPTIMIZE BIG DATA MANAGEMENT AND UTILIZATION DOI Creative Commons

Md Kazi Shahab Uddin,

Kazi Md Riaz Hossan

Academic journal on business administration, innovation & sustainability., Journal Year: 2024, Volume and Issue: 4(3), P. 66 - 78

Published: July 28, 2024

This review examines the implementation of AI-powered data warehouse solutions to optimize big management and utilization, analyzing 25 peer-reviewed articles published over last decade. As organizations increasingly rely on vast amounts for strategic decision-making, traditional warehousing techniques have struggled keep pace with volume, variety, velocity modern data. The integration artificial intelligence (AI) into processes has emerged as a critical advancement, enhancing processing efficiency, accuracy, scalability. study synthesizes findings from literature highlight key benefits such automated extraction, transformation, loading (ETL) processes, real-time analytics, improved quality through advanced cleansing anomaly detection. Additionally, it identifies significant challenges including security risks, complexities, need specialized skills substantial investments. concludes recommendations future research practical applications, emphasizing importance planning robust measures fully leverage AI's potential in revolutionizing warehousing.

Language: Английский

Citations

4
A REVIEW OF UTILIZING NATURAL LANGUAGE PROCESSING AND AI FOR ADVANCED DATA VISUALIZATION IN REAL-TIME ANALYTICS DOI Creative Commons

Md Kazi Shahab Uddin

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(4), P. 34 - 49

Published: July 28, 2024

This review explores the integration of Natural Language Processing (NLP) and Artificial Intelligence (AI) in enhancing data visualization for real-time analytics. In an era characterized by exponential growth data, traditional static visualizations are increasingly inadequate meeting demands decision-making. NLP AI offer sophisticated tools to dynamically interpret visualize turning vast amounts raw information into actionable insights across various domains. paper synthesizes current research, methodologies, applications visualization, highlighting key advancements such as enhanced interpretability, processing capabilities, improved user interaction through natural language queries interactive elements. It also addresses challenges limitations associated with implementing these technologies, including computational complexity, quality issues, ethical considerations. The identifies significant trends future directions, augmented virtual reality (AR/VR) use generative models, which promise further advance field. By providing a comprehensive overview state this aims inform guide research development efforts leveraging technologies more effective efficient data-driven

Language: Английский

Citations

4
BUSINESS MODEL DEVELOPMENT IN THE CIRCULAR BIOECONOMY: A FOCUS ON THE FASHION-TEXTILE INDUSTRY DOI Creative Commons
Vincenzo Basile, Nunzia Capobianco, Roberto Vona

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 144944 - 144944

Published: Feb. 1, 2025

Language: Английский

Citations

0
Advancements in Antimicrobial Textiles: Fabrication, Mechanisms of Action, and Applications DOI Creative Commons
Jonathan Tersur Orasugh, Lesego Tabea Temane, Sreejarani Kesavan Pillai

et al.

ACS Omega, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Within the past decade, much attention has been drawn to antimicrobial textiles due their vast potential for reducing spread of infectious diseases and improving hygiene standards in various environments. This review paper discusses recent studies on preparation methods, modes action, effectiveness against different microorganisms, applications diverse industries. It examines further challenges, including durability, environmental impact, regulatory considerations, looks at prospects developing integrating these novel materials. intends provide a broad-based understanding state-of-the-art technologies emerging trends by existing knowledge highlighting advances this field that contribute improved public health safety.

Language: Английский

Citations

0
Eco-friendly flame retardant and antibacterial finishing solutions for cotton textiles: A comprehensive review DOI Creative Commons
Bekinew Kitaw Dejene, Mulat Alubel Abtew,

Mihret Pawlos

et al.

Journal of Industrial Textiles, Journal Year: 2025, Volume and Issue: 55

Published: March 1, 2025

Cotton (Gossypium spp. ), commonly known as the “King of Fibers,” plays a crucial role in global textile industry because its comfort, breathability, and biodegradability. However, their high flammability presents significant safety risks, particularly fire-prone environments, leading to an urgent demand for effective flame retardants. In addition concerns, lack inherent antibacterial properties cotton makes it susceptible microbial growth, resulting odors fabric degradation. This issue has been exacerbated by COVID-19 pandemic, which heightened public awareness hygiene necessity textiles that minimize contamination. Consequently, there surge need treatments textiles, focusing on solutions are both environmentally friendly. Despite this increasing focus, numerous reviews have examined flame-retardant finishing separately. comprehensive analysis integrates functionalities not yet systematically compiled. review aims fill critical gap consolidating existing literature eco-friendly specifically flame-retardant, antibacterial, dual-functional treatments. It evaluates current state retardants, assesses effectiveness various natural agents, explores innovative synergistic formulations designed enhance resistance performance. also identifies future directions development multifunctional meet evolving demands consumers align with regulatory standards, ultimately contributing safer more sustainable solutions.

Language: Английский

Citations

0
CYBERSECURITY SOLUTIONS AND PRACTICES: FIREWALLS, INTRUSION DETECTION/PREVENTION, ENCRYPTION, MULTI-FACTOR AUTHENTICATION DOI Creative Commons

Ms Roopesh

Academic journal on business administration, innovation & sustainability., Journal Year: 2024, Volume and Issue: 4(3), P. 37 - 52

Published: July 25, 2024

In today's digitally interconnected world, cybersecurity is paramount for protecting sensitive information from sophisticated threats. This literature review examines four key solutions—firewalls, intrusion detection and prevention systems (IDPS), encryption, multi-factor authentication (MFA)—highlighting their roles, advancements, challenges based on 105 articles. Firewalls (n=35), including packet-filtering, stateful inspection, proxy, next-generation firewalls (NGFWs), act as barriers controlling network traffic. NGFWs integrate deep packet inspection application awareness, enhancing security despite complex maintenance issues. IDPS technologies (n=30) have evolved anomaly to AI-integrated systems, improving threat while facing false-positive rates zero-day exploit challenges. Encryption (n=25) ensures data confidentiality, progressing basic ciphers algorithms like AES post-quantum cryptography, though it grapples with computational management complexities. MFA (n=15) enhances through multiple verification factors, evolving passwords biometrics behavioral analytics, yet faces user inconvenience potential bypass methods. A comparative analysis reveals that effectively prevent detect threats but require meticulous management; encryption demands efficient strengthens may encounter resistance. Integrating these solutions within a layered framework provides comprehensive protection, leveraging strengths resilient posture. Case studies affirm multi-layered approaches reduce breaches, underscoring the effectiveness of integrated practices. Continuous innovation, education, adaptive are vital addressing dynamic cyber threats, reinforcing need robust, multi-faceted strategy.

Language: Английский

Citations

2
https://allacademicresearch.com/index.php/AJSTEME/article/view/89 DOI Creative Commons
Janifer Nahar, Nusrat Jahan,

Sadia Afrin Shorna

et al.

Academic journal on science, technology, engineering & mathematics education., Journal Year: 2024, Volume and Issue: 4(3), P. 63 - 74

Published: July 24, 2024

The integration of Artificial Intelligence (AI) and Machine Learning (ML) in the financial sector has brought about a profound transformation decision-making processes, risk management, predictive analytics. This comprehensive study aims to systematically identify analyze foundational theories, emerging themes, research clusters within extensive body AI ML finance literature through an in-depth bibliometric analysis. By meticulously examining vast array publications spanning over two decades, uncovers intricate evolution applications finance, mapping out key areas providing valuable insights into future directions. findings reveal significant accelerating growth application across various domains, notably fraud detection, portfolio algorithmic trading, demonstrating substantial impact transformative potential these technologies. not only charts current landscape but also identifies critical gaps opportunities for exploration, underscoring ongoing maturation this dynamic field.

Language: Английский

Citations

1
BIG DATA ANALYTICS FOR ENHANCED BUSINESS INTELLIGENCE IN FORTUNE 1000 COMPANIES: STRATEGIES, CHALLENGES, AND OUTCOMES DOI Creative Commons
Md Rasel Ul Alam,

Sk Abdur Rahim Shabbir

Academic journal on business administration, innovation & sustainability., Journal Year: 2024, Volume and Issue: 4(3), P. 53 - 65

Published: July 25, 2024

This study investigates the transformative impact of big data analytics and business intelligence on operations strategic decision-making Fortune 1000 companies, with a focus Walmart. Walmart's integration advanced tools has enabled significant optimization across various areas, including inventory management, customer engagement, supply chain operations. Leveraging data, Walmart gained deep insights into behavior, allowing for accurate demand forecasting streamlined operations, which enhance operational efficiency competitive advantage. The highlights use predictive to improve management efficiency, demonstrating how analyzing purchasing patterns preferences reduces stockouts excess inventory, thus boosting satisfaction minimizing costs. Despite its infrastructure, faces challenges in real-time due silos created by vast Enhancing governance practices is crucial ensure quality, security, compliance. Additionally, examines dynamic pricing algorithms adjust prices based market conditions, effectively maximizing sales profitability, aligning previous research benefits retail. Furthermore, broader economic implications data-driven strategies are discussed, noting that while efficient lower benefit consumers, they also pose small local businesses. provides detailed analysis leverage sustain advantage drive success, offering valuable other companies importance technology, organizational culture, achieving sustained success.

Language: Английский

Citations

0