The Role of Artificial Intelligence in Market Analysis : A Case Study in the Maritime Industry
Year: 2025
Type: dissertation
Abstract: This thesis explores how artificial intelligence (AI) can support market analysis in the maritime industry, driven by increasing environmental pressures and regulatory demands for sustainable fuel solutions. This requires maritime companies to make faster, more accurate, and forward-looking decisions. Understanding how AI can enhance both operational decision-making and long-term strategic planning through improved market insights is therefore highly relevant. This research focuses on how firms can utilize AI to transform market data into knowledge and business value. The study addresses this through three research questions structured around organizational context, data transformation into knowledge, and business outcomes. Prior research indicates that maritime companies still rely heavily on intuition rather than structured, data-driven decision-making. To address this issue, the study applies a theoretical framework based on Davenport et al. (2001), emphasizing the organizational capabilities required to convert market data into actionable results. Additionally, the study examines the safe and transparent use of AI, highlighting the role of human–AI collaboration in market analysis practices. The research was conducted as a qualitative case study, based on semi-structured interviews with internal experts from a maritime case company specializing in fuel solutions, and external professionals in AI, data, and market intelligence. Analysis of the findings using the Gioia method provides a key contribution of this study, the dual-structured model for AI-enhanced market analysis. It was formulated from two distinct but complementary approaches to market analysis that emerged as a consistent pattern across the interviews. The model consists of two interconnected layers, continuous monitoring (operational layer) and deep analysis (strategical layer). Continuous monitoring supports operational agility and sales by recognizing relevant signals from industry news, customer activities, and competitor actions through AI-enabled web-scraping and alerts. In turn, deep analysis enhances strategical planning, including Research & Development (R&D) by utilizing databases, customer surveys, and tacit knowledge combined with advanced AI tools, such as Retrieval-Augmented Generation (RAG). Furthermore, this thesis presents a practical framework that supports the adoption of this model, underlining the importance of organizational processes for the implementation strategy. These contributions are particularly relevant for maritime companies seeking to build their AI capabilities in order to generate business value through structured and AI-enhanced market intelligence.
Source: UTUPub (University of Turku)
Author: Taanila, Kaspian
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7005554312