THE IMPACT OF AI-BASED TOOLS ON COMPETITIVENESS AND SUSTAINABILITY IN NICHE SECTORS: A CASE STUDY OF LOCAL DRYING ENTERPRISES
THE IMPACT OF AI-BASED TOOLS ON COMPETITIVENESS AND SUSTAINABILITY IN NICHE SECTORS: A CASE STUDY OF LOCAL DRYING ENTERPRISES

Summary/Abstract: The aim is to explore the potential applications of AI in both competitive analysis and sustainability improvement within a selected local construction industry sector, with a particular focus on niche markets such as drying services. The theoretical contribution of this study is to demonstrate novel applications of AI in strategic management, thereby extending the existing approaches by incorporating the utilisation of analytical tools to support decision-making processes, based on a selected type of software (Local SEO Software). This research employs a case study methodology to examine the utilisation of AI for competitive analysis and sustainability among enterprises, with a particular focus on small and medium-sized enterprises operating in the drying services sector. The study combines quantitative data with qualitative insights to assess how AI-driven tools can enhance competitiveness and sustainability. The findings of this study ascertain whether AI tools (Localo) facilitate a more precise comprehension of the competitive dynamics within the selected companies. It was feasible to discern local competitors and their conduct in terms of competing for visibility on the Google. The research indicates that the utilisation of AI-enabled insights enables local companies to optimise their market visibility, which is a crucial factor in sectors that rely heavily on high-energy processes, such as drying. This article contributes to the growing body of literature on strategic management by examining the dual role of AI in fostering competitive advantage and sustainability, particularly in niche markets that have been relatively underexplored. The study provides insights into the ways in which AI-based tools can be harnessed to not only enhance competitive analysis processes but also to buttress sustainable practices, thereby ensuring long-term viability and a reduction in environmental impact.

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