Artificial intelligence applications for digital sustainability in e-export: An empirical study on the tableware industry

Within the scope of this research, the priority levels of digital sustainability dimensions —economic, environmental, social, technological, and systemic— were examined in relation to export-oriented enterprises operating in Turkey's tableware sector. In this study, the concept of digital sustainability is addressed in a multidimensional manner, encompassing e-export-oriented growth strategies, artificial intelligence-supported digital transformation practices, and the goals of sustainable development. Due to the presence of uncertainty and subjective judgments in the decision-making process, the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method was adopted, and the criteria were evaluated using triangular fuzzy numbers. The research population consists of tableware companies operating in the province of Kütahya that hold potential for e-export, while the sample comprises sector experts with the necessary knowledge to assess strategic digital sustainability practices. In data collection, a pairwise comparison method based on expert judgment was applied, and evaluations were conducted through fuzzified decision matrices. During the analysis process, the opinions of decision-making experts were aggregated using the geometric mean method. The final criterion weights were then calculated by applying Chang's (1996) Extent Analysis Method on the fuzzy comparison matrix. The findings revealed that among digital sustainability criteria, the highest priorities were assigned to economic, technological, and systemic factors. At the sub-criteria level, components such as tax and customs advantages, trade facilitation, efficiency through automation, and stakeholder engagement came to the forefront. This study demonstrates that digital transformation in the tableware sector should be considered not merely as a technological advancement but as a strategic orientation focused on sustainability. It also presents an original, scientifically grounded decision support model for prioritizing digital sustainability criteria at the sectoral level.