Global journal of Business and Integral Security

Data Extraction Approach for Aggregator Platforms

Anand Fadte — 2024-12-04

The digital landscape is rapidly evolving, and aggregator platforms have become crucial intermediaries in sectors such as e-commerce, food delivery, news, job portals, real estate, and education technology (EdTech). These platforms collect and consolidate data from multiple sources, providing users with a unified, accessible interface. However, the efficiency and accuracy of data extraction are critical challenges due to the dynamic nature of web content and the variability in data structures across different websites.
Traditional data extraction methods employed by aggregator platforms often rely on manual processes or basic automation tools, which are not sufficient to handle the complexity and variability of modern web data. These methods can result in significant inefficiencies, such as delays in data aggregation, inaccuracies, and incomplete datasets. This, in turn, affects the reliability and performance of aggregator platforms, leading to potential business risks.

Real-Time AI-Powered Revenue Assurance Technology Adoption Based on the Theory of Reasoned Action

David Tatang Ghogomu — 2024-12-04

Purpose: Empirical investigation of social influence on adoption of a real-time AI-powered revenue assurance technology (RT-AI-RAT) by retail banks in Cameroon.
Methodology: Applied, explanatory, deductive, quantitative and cross-sectional study design. Study instrument psychometric properties tested using Cronbach alpha and exploratory factor analysis. Self-administered questionnaires collected data from participants. Probability-based simple random sampling with a response rate of 14.8% was used. After data screening and regression assumption verifications, GNU PSPP (Release 1.6.2-g78a33a) software employed linear regression for data analysis.
Main Results: The hypothesis was supported in significance (p= 0.05) but not directionally (B= -27). Social influence explained 20% of the effects.
Conclusions: Social influence had a significant negative effect on Cameroon retail banks’ intention to use RT-AI-RAT hence continuing CAATs use. High unawareness of the technology and mal-practice were speculated causes.
Paper Type: Research paper
Keywords: Real-time, Artificial Intelligence (AI), Automation, Audit, Banks, Revenue Assurance, Theory of reasoned action (TRA), Cameroon.

Imagining the Future: Designing Humanity Through Cloning and Eugenics

Noraini Yunus — 2024-12-04

This conference paper delves into the ethical, social and philosophical implications of human enhancement technologies, specifically cloning and eugenics, within Singapore's thriving STEM landscape. Drawing from personal experience with orthognathic cosmetic surgery and inspired by Hypatia's intellectual legacy, this research explores the potential of these technologies to redefine human identity, capabilities and societal structures. The need for breakthroughs in Human Nuclear Genome Editing (HNGE) and alternative approaches is underscored by congenital diseases. To ensure responsible innovation, this paper proposes integrating algorithmic frameworks that prioritise informed decision-making, risk management and individual autonomy, aligning with Hypatia's principles of critical thinking, inclusivity and empathy. As a researcher and aspiring policymaker, this work aims to develop forward-thinking policies that harmonise STEM innovation with human well-being, dignity and self-determination, promoting inclusivity and equitable access. This research envisions a future where genetic advancements serve diverse humanity, advancing social justice and progress in anthropology and beyond. Keywords: genetic engineering, cloning, eugenics, Singapore legislation, ethics, governance, humanity, algorithms

Onboarding in the Humanitarian Sector Using Digital Platforms: The IFRC Global Onboarding Portal Case Study

Bethania Monteforte Sasseron — 2024-12-04

The humanitarian sector faces unique challenges, including the need for rapid mobilisation, cultural diversity and limited resources. Digital transformation, particularly in onboarding processes, offers strategic solutions by streamlining operations, improving efficiency, communication, collaboration and staff engagement, while ensuring alignment with the organisation's mission. This article explores the role of digital platforms, specifically the International Federation of Red Cross and Red Crescent Societies (IFRC) Global Onboarding Portal, in standardising onboarding processes across global teams. In addition, the research highlights the importance of agile project management strategies and human-centred design in the development of the onboarding programme. Future research is recommended to assess the long-term impact of the onboarding programme through longitudinal studies and to explore the potential of artificial intelligence to optimise onboarding processes.
Keywords: Humanitarian Sector, Onboarding Solutions, Digital Transformation, Agile Project Management, Human-Centred Design.

Challenges of Labor Migration: Perception of Domestic/Foreign Workers and Management on Occupational Health and Safety in Croatia

Tomislav Katić — 2024-12-02

Publicly available data shows that a very high percentage of foreign workers are employed in the construction sector in the Republic of Croatia. Labor migration brings challenges and opportunities for economic and social development, but also challenges in the implementation of health and safety measures in the workplace. In order to develop effective safety measures and preventive strategies, it is important to understand how the different groups, e.g. local and foreign workers and management, perceive safety. There are legal frameworks and guidelines for the implementation of health and safety measures to ensure the highest possible level of safety. Within this framework, no distinction is made between foreign workers, local workers and management. Since the perception of safety is a fundamental aspect of workplace safety and plays a key role in protecting the well-being of workers, it is necessary to further investigate how occupational safety and health is perceived by foreign and domestic workers and management in the Republic of Croatia and whether there are differences between these groups. The paper provides an overview and conclusions from the relevant recent research as well as an announcement of empirical research in Croatia.

Impact of Fine-Tuning on Model Training: A Comprehensive Study Using the SQuAD Benchmark

Suresh Kumar Choudhary — 2024-12-02

Purpose - This study investigates the effect of fine-tuning on model training, and the impact of model training on the environment in terms of carbon footprint emissions. As language modeling evolves, we are obtaining complex and large models with a large number of trained parameters. However, only large enterprises are able to train these large models using large datasets. It is not possible for small and mid-size enterprises due to their computation resources capability. This study proposes a fine-tuning model training pipeline for such enterprises to get the same model capability as large enterprises with less number of model parameters training using SQuAD benchmark. The pre-trained BERT base model is incorporated in combination with fine-tuning methods in this study.
Findings - The results explain us that fine-tuned models need less computation time and less number of trainable parameters without losing too much model capabilities compared to the fully trained model, which indirectly helps us to protect the environment as it emits less carbon footprints.

Onboarding in the Humanitarian Sector Using Digital Platforms: The IFRC Global Onboarding Portal Case Study

Bethânia Monteforte Sasseron — 2024-12-02

Identify Consumer Brand Affinity During Point of Purchase Using SEM to Aid Business Growth

Santhosh Francis — 2024-12-02

This research is being executed to understand how the consumer perspective of brand equity based on the success achieved through top-of-mind presence resulting in business profitability. The important question is: What are the key drivers to a particular Brand’s success and failure and how it can be course corrected to achieve the desired outcome by tweaking a particular under-performing driver without any bias. The method involved in identifying the key drivers to enhance Brand equity is called Structural Equation Modeling (SEM).

Generating Recommendation Insights as Part of the Software Upgrade and Decommissions Life Cycle in the Information Technology Industry

Ravikanth Kowdeed — 2024-12-02

As part of Digital Transformation needs, the Organizations are investing more and more in the
Technology and Infrastructure like software upgrades, software renewals, software replacements,
Cloud migrations etc., apart from investment in Business, People, and Processes. In this context, it is
not an easy task for stakeholders to decide whether to go for a software upgrade or to replace it with
another software. There is no unified approach or solution available today which integrates key
system assets data such as Software Versions, Platform Compatibility, Dependent Software versions,
Investment and Operational Costs, Open defects and fixes, Software Performance Metrics and Service
level objectives. Due to this, the so-called decision making is a tedious process that takes time and
effort. This research paper proposes Software Upgrade and Decommissions Life Cycle and outlines
the requirements, design and build approach for generating recommendation insights. This also
proposes using Data Mining and Machine Learning models on the input data sets that are needed to
take a decision on software upgrade or software decommissioning.

Standardizing Emotional Bias to Address Unethical Billing Practices

Prabhat Kumar — 2024-12-02

The proliferation of algorithm-driven billing systems, such as Google Ads and modern electricity meter billing systems, has opened the lid to significant ethical challenges. It will focus on the analysis of billing algorithms in Google Ads and electricity meter systems. The study will analyze the billing algorithm of Google Ads, a system accused of opacity in pricing and the likelihood of overpricing as a result of hidden charges, to find improvements that will increase transparency and standardization. It does apply to electricity meter billing systems, usually prone to estimation errors and some unexpected high bills, in developing measures to ensure accurate and fair billing. The standardized step of this research in carrying out these measures underlines the reduction of bias and enhancement of transparency toward the goal of a fairer environment of billing for consumers.