A STRUCTURAL ANALYSIS OF DIGITAL CUSTOMER ENGAGEMENT DRIVERS AND THEIR INFLUENCE ON CUSTOMER SATISFACTION IN NIGEIA'S PORT LOGISTICS SERVICE ECOSYSTEM
In the rapidly evolving digital economy, customer engagement has emerged as a critical determinant of business success, particularly within complex service ecosystems such as port logistics. In Nigeria, where port operations are vital to trade and economic development, the adoption of digital tools to enhance customer interaction and satisfaction is gaining prominence. This study conducts a structural analysis of the key drivers of digital customer engagement and investigates their influence on customer satisfaction within Nigeria’s port logistics sector. By exploring the influence of digital customer engagement drivers on customer satisfaction in Nigeria’s port logistics service ecosystem, the research aims to provide actionable insights into optimizing digital engagement strategies for improved service delivery and stakeholder experience. To achieve this objective, the main source of data was through primary source with the use of questionnaire. The researcher adopted the survey research design approach and data were collected from 323 respondents drawn from the port logistics service firms’ customers’ base. A total number of 318 copies of the questionnaire were retrieved in useable form representing 98.5 percent of data analyzed using the Simple Regression Model (SRM). Data generated from the study were processed using descriptive and inferential statistics and hypotheses tested at0.05 level of significance. Findings revealed that digital customer engagement drivers had significant influence on customer satisfaction within Nigeria’s port logistics service ecosystem. Thus, the study recommended that the port managers should utilize predictive analytics to deliver proactive services by examining historical customer behavior, shipment patterns, and cargo categories to anticipate future customers’ needs
Institutions
- Akwa Ibom State University (NG)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-29
- DOI
- https://doi.org/10.5281/zenodo.15546277
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00