Posted: February 13th, 2024

Port Selection Criteria from Logistics Service Providers’ Perspective

Port Selection Criteria from Logistics Service Providers’ Perspective: A Case Study of West Africa
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Introduction
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West Africa is a region with a population of over 400 million people and a GDP of about $700 billion. The region is endowed with abundant natural resources, such as oil, gas, gold, cocoa, and timber, and has a growing consumer market. However, the region also faces many challenges, such as political instability, security threats, poor infrastructure, corruption, and trade barriers. These challenges affect the efficiency and competitiveness of the region’s logistics sector, which is vital for facilitating trade and economic development.

One of the key components of the logistics sector is the port industry, which handles about 90% of the region’s external trade. West Africa has about 40 ports along its coastline, ranging from small river ports to large deep-sea ports. However, not all ports are equally equipped or capable of providing quality services to the logistics service providers (LSPs), such as shipping lines, freight forwarders, and cargo owners, who use them. Therefore, LSPs have to make strategic decisions on which ports to use for their operations in West Africa.

The port selection decision by LSPs is complex and involves multiple criteria, such as port location, infrastructure, service quality, cost, security, and connectivity. Moreover, the port selection criteria may vary depending on the type of LSPs, their objectives, and their preferences. For example, a global container carrier may have different port selection criteria from a local freight forwarder or a cargo owner. Therefore, it is important to understand how different LSPs perceive and evaluate the port selection criteria in West Africa.

The aim of this paper is to investigate the port selection criteria from LSPs’ perspective in West Africa using a case study approach. The paper will focus on two countries in the region: Nigeria and Uganda. Nigeria is the largest economy and the most populous country in West Africa, with a GDP of about $450 billion and a population of over 200 million. Nigeria has six major ports along its coastline: Apapa, Tin Can Island, Onne, Port Harcourt, Calabar, and Warri. Uganda is a landlocked country in East Africa with a GDP of about $35 billion and a population of over 40 million. Uganda depends on the ports of Mombasa in Kenya and Dar es Salaam in Tanzania for its external trade.

The paper will use a mixed-methods approach to collect and analyze data from both primary and secondary sources. The primary data will be obtained from semi-structured interviews with LSPs operating in Nigeria and Uganda. The secondary data will be derived from existing literature, reports, statistics, and websites. The paper will use the Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance-Performance Analysis (IPMA) to examine the relationships between the port selection criteria and the port performance from LSPs’ perspective. The paper will also compare and contrast the findings from Nigeria and Uganda to identify any cross-national differences or similarities.

The paper is organized as follows: Section 2 reviews the relevant literature on port selection criteria and port performance measurement. Section 3 describes the research methodology and data collection process. Section 4 presents the results and discussion of the data analysis. Section 5 concludes the paper with some implications and recommendations for policy makers and practitioners.

Literature Review
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Port Selection Criteria
Port selection is defined as “the process by which shippers or their agents choose one or more ports for their shipments” (Tongzon & Sawant 2007). Port selection is an important strategic decision for LSPs because it affects their operational efficiency, service quality, customer satisfaction, and profitability. Port selection is also influenced by various factors at different levels: macro-level (e.g., political, economic, social), meso-level (e.g., market structure,

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