Strategy Selection for the Digitization of Traditional Industries in Guangxi: A Machine Learning Enhanced SWOT-AHP Approach

The digitization of industries has been given great importance in augmenting productivity and promoting economic growth. Nonetheless, most of the research concerning the digitalization strategy for traditional industries in Guangxi used the qualitative methodology. In this article, we propose a machine learning SWOT-AHP integration to optimize the decision-making. First, several qualitative factors that affect industry digitization in Guangxi were derived using SWOT analysis. The next step is to refine the pairwise comparison matrix using a machine learning algorithm such as random forest regression, thus imparting weights to the criteria more accurately and overcoming the judgement inconsistencies of the experts. Based on the results of the analysis, the central point of the strategy quadrilateral lies at the fourth quadrant, indicating the adoption of an ST Strategy (Strength-Threat Strategy). The current study enriches the literature dedicated to the data-driven-formulation strategy and gives practical insights regarding the digital transformation of traditional industries in Guangxi.