Global journal of Business and Integral Security

NEUTRALITY IN THE DIGITAL AGE: ADAPTING SWISS GOVERNANCE MODELS TO SECURE PAKISTAN’S CRITICAL INFRASTRUCTURE AGAINST GLOBAL CORPORATE HEGEMONY

Umar Iqbal Butt — 2026-09-25

Pakistan legally owns its most consequential national assets yet does not operationally control them. The SCADA systems governing the Reko Diq mining complex and the national energy grid are managed by foreign entities under foreign jurisdictions, a condition this article terms Digital Suzerainty. Using a comparative case study, the article benchmarks Pakistan’s critical infrastructure governance against Switzerland’s National Cyber Strategy. Three findings emerge. First, Pakistan’s Prevention of Electronic Crimes Act lacks data residency mandates, sovereign key management and vendor liability frameworks. Second, both Reko Diq and the CPEC energy grid exhibit dependency configurations associated with state-sponsored operational freeze attacks. Third, the proposed Pakistan Sovereign Stack offers a phased, technically specific blueprint for Strategic Decoupling that is reproducible across resource-dependent Global South economies.
Keywords: Digital Sovereignty, Critical Infrastructure, Pakistan, Switzerland, CPEC, Pakistan Sovereign Stack.

“FROM DR. MEDICUS RATIONALIS TO BRAND RESONANCE: A FRAMEWORK FOR EMOTIONAL BRANDING IN PHARMACEUTICAL MARKETING

Alexandros Athanasiou — 2026-09-22

In pharmaceutical marketing, data has long been the core essence of brand communication. The industry’s default assumption, what this paper terms “Dr. Medicus Rationalis”, presumes that healthcare professionals are purely rational decision-makers influenced primarily by clinical evidence. The assumption that prescribing decisions are solely rational, based on factual information, is challenged by contemporary research.
This research aspires to have significant implications for pharmaceutical companies by highlighting the significant impact that emotions can have on physicians' prescribing choices and offer practical recommendations to pharmaceutical companies on how to adapt their marketing strategies in a way that can resonate more effectively at an emotional level with the healthcare providers. The framework consists of 30 practical applications and was developed through a mixed multi-method doctoral research approach. The findings suggest that incorporating emotional elements into pharmaceutical marketing, presents considerable opportunities to reinforce brand differentiation.
Keywords: Emotional branding, Pharmaceutical marketing, Brand Resonance, Prescriber decision-making.

WHY ANCILLARIES SHOULD DRIVE PRICING STRATEGY: A PRACTITIONER’S VIEW

Rahaman Sheriff — 2026-09-18

Airlines have been lately earning a large share of revenue from ancillaries (Bags, seats, bundles, and loyalty add-ons). This commentary argues that the pricing teams should start treating ancillaries as first class pricing inputs to optimize the total passenger yield, instead of optimizing fares in isolation. This paper covers industry evidence and a live pricing experiment, with three practical recommendations, which is making expected ancillary value visibly in pricing decisions, test ancillary offers with small A/B experiments and keeping bundles simple and transparent for customers. Short, actionable steps are provided so commercial teams can start capturing ancillary value without major systems overhaul.
Keywords: Ancillaries; airline pricing; revenue management; dynamic pricing; experimentation; offer retailing; customer experience

Enabling Sustainable AI

Frank Soans — 2026-06-10

Deep tech and the world of AI have been rapidly changing the market share and is one of the most focused industries. While opportunities are great, the pit falls maybe likewise. One key element in avoiding pit falls is the need to develop AI with a sustainable approach or building Sustainable AI. AI is dependent on human intelligence and would undergo similar learning cycles to that of humans such as learning, unlearning, and new learning as part of its machine learning ability. This cycle would
ensure it is relevant based on new data and information that is made available, discovered or generated, be it by humans, nature, industry or by AI itself. It would also need an active supply chain, one that is sustainable to ensure appropriate learning and refresh to ensure the improvement continues. The processes applied from design to decline would be key in creating Sustainable AI. To ensure this process is viable and sustainable, principles like design thinking and systems thinking maybe critical right from
the design process, through the steps carried out in the AI build and its continued maintenance to ensure a more humane and wholistic development of AI. This design approach needs to be profitable, inclusive and circular to ensure stakeholder objectives, human social factors, economic requirements and environmental impacts are addressed.
Keywords: Sustainability, AI, Machine Learning, Artificial Intelligence, environmental, societal, economy, design, Sustainable AI.

Lowering Technical Barriers in Machine Learning Education: A Usability Evaluation of an Integrated Analytics Framework

Antonios Konomos — 2026-05-07

The increasing role of data analytics and machine learning (ML) across different fields has created a strong need for educational tools that support both theoretical understanding and hands-on practice. Although Python is widely used as the main programming language for data analytics, many students and
early-stage researchers find it difficult to use effectively because of steep learning curves in programming, statistics, and ML frameworks. This study introduces MLapi, an API-based machine learning tool designed to reduce technical barriers and make ML methods more accessible in educational and applied analytics settings. MLapi uses a three-tier architecture that links Microsoft Excel as the user interface with a Python-based analytics engine, allowing users to run statistical analysis and ML algorithms while viewing the underlying Python code in Jupyter Notebook format. To assess usability, an empirical study was conducted using the System Usability Scale (SUS) with data analytics professionals. The evaluation included reliability testing, hypothesis testing across demographic groups, and Principal Component Analysis to identify usability dimensions. Results show high overall usability, strong internal consistency, and no significant differences between demographic groups, indicating that MLapi provides an inclusive and user-friendly learning environment. These findings suggest that MLapi can serve as both an educational tool and a practical analytics solution, helping to create accessible ML learning environments and encouraging broader participation in data analytics education.
Keywords: Machine learning, Data Analytics, System Usability Scale, API-based Architecture, HumanComputer Interaction, Principal Component Analysis

Mind the Gap: A Review of Machine Learning Tools in Educational Settings

Antonios Konomos — 2026-01-23

This review examines a wide range of machine learning (ML) tools used in educational settings, focusing on their effectiveness in teaching both ML concepts and Python programming. The analysis covers commonly used platforms such as Google Colab, TensorFlow, Keras, Scikit-learn, Teachable Machine, Create ML, WEKA, KNIME, and Open Mind, assessing their educational value and limitations. The study finds that while low-code and no-code tools lower the barrier to entry for ML education, they often lack the flexibility and depth needed to support the development of advanced analytical and programming skills. In contrast, tools like Python libraries provide robust learning experiences but demand a higher level of prior knowledge. The research identifies a gap between accessible tools and those capable of fostering Python proficiency, emphasizing the need for integrated solutions that balance usability and technical rigor. This work contributes to the discourse on enhancing ML education through strategic tool selection.

A Decision-Making Framework for Prioritizing AI Adoption Across Enterprises

Gustav Lindéus — 2026-01-23

This paper addresses the increasing challenge of how to select and prioritize generative AI initiatives
when technologies develop faster than governance, compliance, and funding processes. We propose the
GAIQ framework: a design-science-based, gate-driven model for qualifying GenAI use cases along
three dimensions, namely, PVI, TFR, and ERC. The model structures decision-making through a SEA
sequence of scanning, evaluation, and activation and applies weighted thresholds so that use cases that
are strategically attractive but weak in ethics or technology cannot advance. Two complementary
instruments, NEXA and NOVA, extend the framework to investment decisions. Validation on simulated
enterprise scenarios shows that GAIQ produces more consistent, auditable, and business-aligned
recommendations than generic AI maturity models, thereby closing the gap between high-level AI
strategy and operational implementation.

A Petrel for the Digital Storm

Lakshmi R Rajagopal — 2026-01-15

The world we live in today is fascinating, we are at the cusp of the fourth and fifth industrial revolution. It took us almost three centuries to get here since the first industrial revolution, the good part is that we will not have to wait for an equal period to experience the subsequent industrial revolutions. The pace and intensity of change is unprecedented and gives one the feeling of being in a sci-fi movie. Vectors shaping the future of work are complex, nuanced and multi-dimensional requiring us to adopt varied strategies so as to thrive in the current order. It requires us to transcend into higher maturity levels of change navigation continuum - to become change architects for our personal selves. Being a change architect would amplify the vector qualities required to sense-make the future. It would help optimise the efforts and energy required to thrive in the future through materiality, intentionality and directionality. This paper takes inspiration from nature, our biggest teacher on how humans can become better change architects to thrive in the future.

Harnessing Artificial Intelligence: Balancing Opportunity with Ethical and Regulatory Responsibility

Glenn Chilcott — 2026-01-15

Artificial intelligence (AI) is poised to deliver transformative economic and societal benefits, with
projections suggesting it could contribute up to $15.7 trillion to the global economy by 2030.
Generative AI alone is expected to create trillions of dollars in annual value across industries.
Yet these opportunities are accompanied by profound ethical, regulatory, and governance
challenges, including bias, privacy risks, market concentration, and environmental impacts. This
paper examines the opportunities and risks of AI, the mechanisms for mitigating those risks
through legislation, regulation, and organisational governance, and the importance of
embedding ethical principles in AI’s design and deployment. It concludes with an assessment of
recent developments and forward-looking predictions for the next one to five years, underscoring
the urgent need for a coordinated global response that balances innovation with responsibility.

Future-Ready Youth Business Leaders: Gender-Based Competencies for the X.0 Wave Generation

Hamid Mattiello — 2026-01-15

The accelerating convergence of digital transformation, sustainability, and technological innovation requires a new generation of youth business leaders equipped with ethical, culturally aware, paradigm-shifting, and gender-sensitive competencies. This study applies the X.0 wave theory as a comprehensive framework to understand societal, technological, and economic evolution and how successive business and societal revolutions reshape leadership requirements (Mattiello, 2024; Doost Mohammadian, 2022; Mattiello, Wittberg and Castro, 2022, November). It examines gender-based competencies essential for developing future-ready leaders capable of navigating digital, green, and human-centered economic transitions (Schwab, 2016; Schwab and Davis, 2018; OECD, 2025; Durani, 2025; Mansour et al., 2024). The framework identifies key competencies, including digital fluency, gender competence, entrepreneurial and strategic skills, and sustainable ethical leadership, using cross-cultural surveys, case studies, and simulation-based assessments (Mattiello, Mattiello and Wittberg, 2025, April; Mattiello and Mattiello, 2025b; Brooks, Tse, Wright and Burdett, 2024; Mattiello, Wittberg, Castro and Langari, 2022, March). These competencies, combined with ethical governance and inclusive leadership, enable youth to respond effectively to Industry 5.0 and emerging Society 6.0 challenges (Mattiello and Domann, 2024; Henderikx and Stoffers, 2023; Held, Heubeck and Meckl, 2025; Mladenova, Vladimirov and Harizanova, 2025). Findings show that integrating ethics, digital skills, and gender-sensitive practices enhances leadership effectiveness, resilience, and inclusivity, offering actionable guidance to cultivate future-ready leaders who drive sustainable and advanced business ecosystems (Mattiello, Alijani, Rahimi Moghaddam and Ameri, 2024; Doost Mohammadian and Rezaie, 2020; Rüdiger, Köchli, Hunter and Mvunelo, 2025; UN Youth Office, 2025; Avice Huet, 2023).