Exploring the impact of Big Data analytics capability on port performance: The mediating role of sustainability
type: CreativeWork
description: Many ports are redefining business processes and operations by adopting digital technologies. These can help them to provide efficient and competitive port operations and meet the growing demand for comprehensive port logistics services. Digital technologies provide a harvest of immense amounts of data, known as Big Data. Port management needs the capability to store, process and analyse Big Data to provide meaningful information and thus to maximise organisational performance. Furthermore, one of the most important trends in port development is increased sustainability awareness by regulators and customers. Port managers can employ Big Data technology to reduce environmental pollution and use resources more efficiently, improving the sustainability of ports. Resource-based theory provides a useful theoretical framework to investigate these issues, including the impact on port performance. There is some evidence that port sustainability has a mediating role in the association between BDAC and port performance. However, more research is needed to investigate the association between BDAC and port performance and to explore the mediation role of port sustainability. To address this research gap, this thesis employs a multi-phase approach to investigate the impact of BDAC on port performance and the role of port sustainability in this context. In phase one of the empirical study, a conceptual model for the structural relationship between BDAC, port sustainability and port performance was developed by examining the existing research literature. After a pilot survey to examine the validity and reliability of the survey instrument, a survey was conducted in the world’s top 50 ports, which provided 175 valid responses for assessing the model. The results from these questionnaires were analysed by Partial Least Squares Structural Equation Modelling (PLS-SEM). Analysis of the collected data revealed four main findings. Firstly, this study provides evidence that managerial ski…
abstract: Many ports are redefining business processes and operations by adopting digital technologies. These can help them to provide efficient and competitive port operations and meet the growing demand for comprehensive port logistics services. Digital technologies provide a harvest of immense amounts of data, known as Big Data. Port management needs the capability to store, process and analyse Big Data to provide meaningful information and thus to maximise organisational performance. Furthermore, one of the most important trends in port development is increased sustainability awareness by regulators and customers. Port managers can employ Big Data technology to reduce environmental pollution and use resources more efficiently, improving the sustainability of ports. Resource-based theory provides a useful theoretical framework to investigate these issues, including the impact on port performance. There is some evidence that port sustainability has a mediating role in the association between BDAC and port performance. However, more research is needed to investigate the association between BDAC and port performance and to explore the mediation role of port sustainability. To address this research gap, this thesis employs a multi-phase approach to investigate the impact of BDAC on port performance and the role of port sustainability in this context. In phase one of the empirical study, a conceptual model for the structural relationship between BDAC, port sustainability and port performance was developed by examining the existing research literature. After a pilot survey to examine the validity and reliability of the survey instrument, a survey was conducted in the world’s top 50 ports, which provided 175 valid responses for assessing the model. The results from these questionnaires were analysed by Partial Least Squares Structural Equation Modelling (PLS-SEM). Analysis of the collected data revealed four main findings. Firstly, this study provides evidence that managerial ski…
author: Xie, Xiaotian
language: eng
keywords: Big Data analyitcs capability, Sustainability, Supply chain management, Port performance
date published: 2023-01-01T08:00:00Z
date modified: 2026-07-24T03:49:48Z
provider: University of Plymouth
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Plymouth