Supply chain performance in transport logistics: An assessment by service providers

Abstract

This study presents an assessment of supply chain performance (SCP) in transport logistics by service providers in the transport logistics industry in Hong Kong. The industry is broadly defined as encompassing firms involved in the business of serving the physical flows of goods from a point of origin, i.e., shippers, to a point of destination, i.e., consignees, in a supply chain. These firms include those in sea transport, freight forwarding, air transport and third-party logistics services. A cross-sectional survey was conducted with firms in the industry to evaluate their perceived SCP in transport logistics and the attached importance from both cost and service perspectives. The study findings provide managerial insights for firms in the industry to understand their SCP in transport logistics and benchmark areas for performance improvement.

An Empirical Taxonomy for Logistics Service Providers

“…This response rate is comparable to those obtained in previous studies of a similar nature (e.g. Lai and Cheng 2003).…”

“…To capture this market opportunity, many LSPs have taken the initiative to offer a wider variety of logistics services. One of their important decisions concerns the extent to which they should expand their service capability and improve their service performance (Lai and Cheng 2003).…”

The effect of acquisition moves on income, pre-tax profits and future strategy of logistics firms

“…A major decision concerns the extent to which they should improve their service performance and expand their service capability (Lai & Cheng, 2003). Performance measurement is an important approach in the logistics service supply chain (LSSC), which can improve the competitiveness of the overall supply chain.…”

Improving the execution of supply chain management in organizations

“…The importance-performance analysis stems from the marketing discipline and is a technique that is often applied for strategy formulation in service settings (see Martilla and James, 1977 or Lai and Cheng, 2003). The IPA is a tool with which an existing performance level of a variable, e.g.…”