International Journal of Case Studies (ISSN Online 2305-509X)

VOLUME 15, ISSUE 3
IMPACT FACTOR 4.428

1) Using AI Tools to conduct Investment Research on Emerging Technology
Author Details: ⁽¹⁾ Joshua ARJANTO ⁽²⁾ CHEN Xiaojing ⁽³⁾ Shiyou HU ⁽⁴⁾ Asher Ethan KOH  ⁽⁵⁾Muhammad Khaizuran Bin MOHAMAD ROSLE ⁽⁶⁾ Lawrence LOH ⁽⁷⁾ Tim ZHANG ^{(1) (2) (3) (4) (5) (6)}National University of Singapore ⁽⁷⁾ Edge Research Pte. Ltd
Abstract:
This case study examines how large language models (LLMs) including ChatGPT, Gemini, and DeepSeek can systematically augment the investment research process across five emerging-technology sectors: Artificial Intelligence, Robotics, Quantum Computing, Space, and Fusion. The analysis evaluates LLMs not as end-to-end automation, but as accelerators within a governed, human-in-the-loop workflow. Across sector onboarding, multi-lingual discovery, numeric extraction, and first-draft synthesis, LLMs reduced mechanical workload by broadening source coverage and enabling faster iteration. However, the evidence indicates that human judgment remains indispensable for causal reasoning, credibility assessment, evidence weighting, and final investment interpretation; LLMs shift analyst effort but do not replace it. To improve evidence hygiene at scale, the case describes a Python-based fact-checking pipeline that automates link reachability, publication-date extraction, and AI-generation risk screening, later extended into a low-code web interface. The workflow reduced verification time from 4.3 hours to 1.25 hours per 50 links (a 71% reduction), with projected savings of over 90% under full integration of headless browsing and GPTZero API scoring. In parallel, a structured source database with over 250 LLM-cited records (graded by recency and credibility) enabled reproducible evaluation of model outputs and surfaced common failure modes such as hallucinations, outdated citations, and contextual drift. Overall, the case study demonstrates that LLMs are most effective as structured force multipliers when paired with rigorous verification tooling and human oversight
Keywords: investment research, large language models, due diligence, source verification, hallucination risk, reproducibility, artificial intelligence
[Download Full Paper] [Page 01-34]
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2) African Renaissance and the Reclamation of Identity (Voices, Visions, and Resistance in Anglophone African Literature)
Author Details: AMADOU BOUNTY DIALLO Cheikh Loundou-Université Abdou Moumouni de Niamey | Département d’Anglais
Abstract:
this article examines how the concept of an African Renaissance — understood here as the sustained drive toward cultural self-determination, civilizational renewal, and psychological decolonization — shapes and is shaped by Anglophone African literary production from the late colonial period to the present. Through close reading of selected works by Chinua Achebe, Ngugi wa Thiong’o, and Wole Soyinka, the article argues that the literary text is not a reflection of Renaissance aspirations but one of the primary arenas in which those aspirations are contested, clarified, and sometimes fundamentally revised. Particular attention is paid to the entangled questions of narrative authority, linguistic sovereignty, gendered selfhood, and diasporic identity that run through this tradition. Instead of treating the Renaissance as an accomplished program, the article insists on its unfinished and internally contested character: the writers examined here agree on very little beyond the conviction that the story of Africa must be told differently, and that literature is where that retelling begins.
Keywords: African Renaissance; Anglophone African literature; postcolonial criticism; decolonization; linguistic sovereignty; cultural identity
[Download Full Paper] [Page 35-42]
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