A critical examination of the impact of big data analytics capability on container port performance

The performance of container ports is increasingly being hampered by port congestion, strict adherence to environmental regulatory frameworks, and inefficiency of border control agencies. Anecdotal evidence indicates that advanced analytics and digitalizing container ports holds much promise to mitigate these challenges. At the same time, a lack of empirical evidence about the effects of big data analytics capability (BDAC) is limiting understanding of how port managers can leverage this novel capability. This study draws on the resource-based view and stakeholder theory to develop and test a model that describes the resources to implement BDAC and subsequently improve four dimensions of port performance (i.e., service quality, operational efficiency, sustainability, and financial performance). We test our research hypotheses using survey data from 175 responses gathered from international container ports that have applied big data analytics. The results support our hypotheses and advance understanding by indicating that BDAC can improve these dimensions of port performance. Specifically, financial performance gains the greatest improvements, whereas operational efficiency gains the least improvements. We provide a comprehensive port assessment framework with four principles and 11 associated key performance indicators. This study illuminates the critical role of tangible, intangible, and human resources in establishing BDAC at the port community level. It also enhances knowledge for port authorities, terminal operators, and other public or private stakeholders of container ports.