This paper aims to measure the relative efficiency of liner shipping companies in terms of operational and financial performance and further investigates the impact of strategic and operational management on efficiency performance. A two-stage Data Envelopment Analysis (DEA) approach is employed combining DEA and Tobit regression, which has been extensively used in various research areas. 14 liner shipping companies from the top 20 container lines in terms of fleet capacity were included in this analysis. The results suggest that the firm size (in terms of TEU capacity), ship size, the ratio of chartered vessels, use of new vessels, and the formation of alliances all make a positive contribution to the financial performance of liner shipping companies. Ship age and ship type did not show a significant contribution to the financial performance and, for the operational performance, any of these determinant factors were not significant. This analysis is able to provide container shipping companies with information on the managerial and strategic implications of how managerial options influence operational and financial performance. In addition, maritime researchers will benefit from this study, measuring the efficiency of container shipping companies and the factors that influence efficiency, as this study is the first to investigate and model factors of relative efficiency of container shipping companies to the authors’ knowledge.

Purpose: The purpose of this paper is to evaluate logistics service quality using the Kano’s service quality model in the logistics-triadic context. Design/methodology/approach: This study undertakes a survey research in semiconductor manufacturing equipment (SME) industry. Logistics service quality is categorized using Kano’s classification and a comparison is made of the perception of three sample groups who are SME firms, semiconductor manufacturers (SMs) and third-party logistics (TPL) providers. Findings: Several attributes of logistics service quality are evaluated as “Must-be” quality which does not contribute to customer satisfaction, indicating existence of the non-linear relationship between some logistics service quality attributes and customers’ satisfaction. The group comparison reveals that TPL firms perceive most quality attributes as “Attractive” and “One-dimensional” whereas SMs and SME firms perceive more attributes as “Must-be.” Research limitations/implications: Logistics service quality elements should not be used in the same way assuming the same effect of logistics service elements on customer satisfaction. It should be also noted that logistics service quality attributes have different effect on satisfaction according to the positions in the logistics triad. Practical implications: This paper provides SME firms with useful information on how to manage their logistics service quality to improve customer satisfaction. SME firms and TPL providers need to arrange a collaborative format where logistics service quality is regularly monitored and three members discuss solutions to improve their quality performance. Originality/value: This study is a rare empirical investigation to actually assess and compare perception on logistics service quality among the entities in a logistics triad. This study applies the Kano model to the triadic relationship in logistics service provision, which may be the first attempt to the authors’ best knowledge.

This paper uses a structured literature review approach to investigate how seaports have been studied during the last three decades (1980s–2000s), and to provide a detailed analysis of seaport-related research during this period. To this end, 840 academic papers of relevance were identified. This paper develops a structured analysis of the relevant literature with general trends and research sub-themes being analysed on a decadal basis. In addition, consideration is given as to how the identified trends and research themes have reflected the evolution of seaports. It is shown that the scale of research related to seaports increased substantially during the 2000s, and that seaport research has become a dominant theme in the area of maritime economic studies. It is also clear that there has been a diversification of research with several new themes emerging, reflecting the evolution of the port industry such as the changing role of seaports in supply chains and logistics.

The evolution of the single-hub container system in Southeast Asia into a multi-hub system, with several emerging container ports serving deep-sea container vessels and forming their feeder service network, may result in intense competition in the region and a transformation in the ports’ roles. Thus, major ports in the region have sought to enhance their competitiveness by offering improved cargo handling capabilities, well-developed infrastructure, and modernised facilities as well as increased service coverage and connectivity to more countries both directly and indirectly. Several major container ports in the area have taken full advantage of competitiveness to become new hub-ports in the area. To understand the dynamics of competition in this rapidly developing region more clearly, this paper presents an evaluation of connectivity of major ports. In addition, the competitiveness of the top ten Southeast Asian container ports is evaluated using the TOPSIS method and K-mean cluster analysis. The results indicate that the top ten ports are categorised into three groups, and while Singapore (Group 1) takes the most advantage of its connectivity, ports in Groups 2 and 3 may be able to enhance competitiveness by developing cargo handling facilities and infrastructure.