With the globalization of the world economy, the container port industry is becoming
increasingly important. This research is motivated by the contrast between the ever mounting
importance of the contemporary container port industry and the sparsity of
scientific and in-depth research of the economic theories that underpin it. Despite the
paramount importance of the container port industry for globalization and international
trade, many fundamental economic theories under pinning the container port production
remain unknown and deserve to be thoroughly investigated. From a theoretical point of
view, very few attempts have thus far been made to apply traditional economic theories
to the container port industry.
This research is also motivated by the vital role played by efficiency measurement in any
sort of production and the dearth of such studies in the container port industry.
Traditional approaches are confined to partial measures of productivity and not
sophisticated enough to reflect the complexity of contemporary container port production
and to provide enough insights on management or policy implications. In recent years,
two leading approaches to measuring efficiency, Data Envelopment Analysis (DEA) and
Stochastic Frontier Analysis (SFA), have been occasionally applied to ports or to the
container port industry in order to measure their efficiency. However, the extant research
in this aspect is far from sufficient. Among other reasons, the existing corpus of research
is either based on strong assumptions, or has ignored the great variety and diverse nature
of the available data (such as cross-sectional or longitudinal data)
Against this background, this research contributes to the existing literature in three ways.
First, the economic theories under pinning the container port production (such as the
relationship between ownership, competition and port efficiency) are not only analysed
by applying traditional economic theory (in particular the industrial organisation theory)
but also examined empirically by deriving scientific estimates of efficiency. Most work
in this aspect is original and, potentially, makes an important contribution to the
establishment of central government policy on port investment, policy and governance.
Secondly, for the first time, comprehensive comparisons of alternative approaches to
efficiency measurement are conducted for the container port industry. These approaches
include the two most well-known and commonly applied, Data Envelopment Analysis
(DEA) and Stochastic Frontier Analysis (SFA), as well as some other important
alternatives, such as the Free Disposal Hull (FDH) method. In addition, consideration is
given to the use of panel data and to a random- and fixed-effects model. Due to the
individual strengths and weaknesses associated with the various approaches to efficiency
measurement, this sort of comparative study represents both a significant and necessary
contribution to both the theoretical and empirical aspects of contemporary efficiency
measurement. Finally, this study provides in-depth policy implications and managerial
insights for China's government to optimize the future development of its port sector to
the benefit of its wider economy and social welfare maximization.