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1 – 10 of 169Majid Eskafi, Milad Kowsari, Ali Dastgheib, Gudmundur F. Ulfarsson, Poonam Taneja and Ragnheidur I. Thorarinsdottir
Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose…
Abstract
Purpose
Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables.
Design/methodology/approach
Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable.
Findings
This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput.
Originality/value
Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.
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This paper analyses the determinants of transport demand for maritime container transport. Such an analysis is relevant, among others for port planning, since port expansion plans…
Abstract
This paper analyses the determinants of transport demand for maritime container transport. Such an analysis is relevant, among others for port planning, since port expansion plans are based on forecasts. Inevitably, different opinions about the future development of (container) transport flows exist, and decisionmakers are confronted with uncertainty. This paper analyses the variables of container transport demand. Seven variables are identified, four related to the overall volume of trade and international transport flows (the GDP, export quote of economies, the direction of trade and the value density of trade) and three related to the containerised proportion of transport flows (the containerisable share of transport flows, the containerisation rate and the share of shipping in international trade). The rise of containerised transport flows from 1980 to 1995 is based on different 'underlying factors'. The future development of the variables is highly uncertain, and a 'extrapolation' of the high growth rates of the past, is not likely to lead to a good forecast for the future. Thus, decision-makers confronted with the uncertainty about future trade flows, should try to maximise flexibility in port planning.
Liu-Liu Li, Young-Joon Seo and Min-Ho Ha
Seaports are a signifier for the world economy and international trade. Notwithstanding the considerable role of Chinese ports in global trade, only few studies have explored the…
Abstract
Purpose
Seaports are a signifier for the world economy and international trade. Notwithstanding the considerable role of Chinese ports in global trade, only few studies have explored the efficiency of Chinese container terminals. Furthermore, studies on Chinese port efficiency has typically centered on port-level analysis, not terminal level. Therefore, this study aims to examine the operation efficiency of Chinese container terminals.
Design/methodology/approach
This study uses super-efficiency data envelopment analysis (SE-DEA) approach. SE-DEA is superior than basic DEA model because it is feasible for categorizing and ranking the efficiency of container terminals more accurately and comprehensively. In the basic model, if the several decision-making units (DMUs) are efficient, the efficiency value of them is “1.” However, in the SE-DEA model, the most efficient DMU is over “1.” Based on the level of container throughput in 2018, the top 20 Chinese container terminal companies were selected. Various production quotas were selected as inputs, while the container throughput was considered output.
Findings
The findings show that Terminal Shanghai Mingdong Container Terminal Co., Ltd. was ranked 1, followed by Shanghai Shengdong International Container Terminal Co., Ltd., Shanghai International Port (Group) Co., Ltd. and Yidong Container Terminal Branch.
Originality/value
This study contributes to providing some insights into Chinese container terminal industry to augment the efficiency. This study also provides practical and policy implications (e.g. better terminal operations) for container terminals.
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Tomoya Kawasaki, Takuma Matsuda, Yui-yip Lau and Xiaowen Fu
In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container…
Abstract
Purpose
In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts.
Design/methodology/approach
The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019.
Findings
In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects.
Originality/value
Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.
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The purpose of this paper is to empirically examine the relationship between intensity of competition and technical efficiency of large European container ports, accounting for…
Abstract
Purpose
The purpose of this paper is to empirically examine the relationship between intensity of competition and technical efficiency of large European container ports, accounting for regional diversities and spatial aspects of inter-port competition.
Design/methodology/approach
The analysis consists of applying a stochastic production frontier approach to a dataset of 77 large European container ports over the period 2002-2012, with inefficiency terms simultaneously modeled as a function of (among other factors) a constructed index of competitive intensity at different spatial levels.
Findings
The results indicate that there is no significant negative effect of competitive intensity on efficiency. In fact, for competing European ports within a proximity of 300 km, a higher level of competition is found to be associated with a higher level of technical efficiency.
Originality/value
The originality of the paper stems from its particular focus on European port regions and its novel findings in this context, which have implications for the discussions regarding pro-competitive port policy and regulation in the European Union.
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The real estate industry has experienced frequent changes in corporate executives in recent years. A total of 147 A-share listed firms witnessed a total of 191 corporate…
Abstract
Purpose
The real estate industry has experienced frequent changes in corporate executives in recent years. A total of 147 A-share listed firms witnessed a total of 191 corporate executives' departure. This wave of corporate executive departures is significantly different from previous waves. This study aims to examine whether industry evolution influence the characteristics of corporate executives? If so, then how?
Design/methodology/approach
Drawing on upper echelons theory, this study analyzed the effects of industry life cycle on the characteristics of corporate executives. The data of A-share listed companies in the textile, real estate and computer industries in China from 1992 to 2014 were collected.
Findings
There are significant differences in the characteristics of corporate executives that match the life cycles of different industries. Companies at the growth stage in the life cycle of an industry were more likely to select and appoint younger corporate executives with political capital, peripheral functions and output functions, whereas companies at the maturity stage were more likely to select and appoint older corporate executives with throughput functions.
Originality/value
By using the upper echelons theory as a starting point, this study analyzed the effects of industry life cycle on corporate executive's characteristics. The research findings offer theoretical implications for the upper echelons theory and provide managerial implications.
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Veerachai Gosasang, Tsz Leung Yip and Watcharavee Chandraprakaikul
This paper aims to forecast inbound and outbound container throughput for Bangkok Port to 2041 and uses the results to inform the future planning and management of the port’s…
Abstract
Purpose
This paper aims to forecast inbound and outbound container throughput for Bangkok Port to 2041 and uses the results to inform the future planning and management of the port’s container terminal.
Design/methodology/approach
The data used cover a period of 16 years (192 months of observations). Data sources include the Bank of Thailand and the Energy Policy and Planning Office. Cause-and-effect forecasting is adopted for predicting future container throughput by using a vector error correction model (VECM).
Findings
Forecasting future container throughput in Bangkok Port will benefit port planning. Various economic factors affect the volume of both inbound and outbound containers through the port. Three cases (scenarios) of container terminal expansion are analyzed and assessed, on the basis of which an optimal scenario is identified.
Research limitations/implications
The economic characteristics of Thailand differ from those of other countries/jurisdictions, such as the USA, the EU, Japan, China, Malaysia and Indonesia, and optimal terminal expansion scenarios may therefore differ from that identified in this study. In addition, six particular countries/jurisdictions are the dominant trading partners of Thailand, but these main trading partners may change in the future.
Originality/value
There are only two major projects that have forecast container throughput volumes for Bangkok Port. The first project, by the Japan International Cooperation Agency, applied both the trend of cargo volumes and the relationship of volumes with economic indices such as population and gross domestic product. The second project, by the Port Authority of Thailand, applied a moving average method to forecast the number of containers. Other authors have used time-series forecasting. Here, the authors apply a VECM to forecast the future container throughput of Bangkok Port.
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Ming-Miin Yu, Bo Hsiao, Shih-Hsun Hsu and Shaw Yu Li
This paper presents an alternative approach to evaluating the overall efficiency and performance of Taiwanese container ports. Specifically, a parallel activity with series…
Abstract
This paper presents an alternative approach to evaluating the overall efficiency and performance of Taiwanese container ports. Specifically, a parallel activity with series structure concept in the form of data envelopment analysis (MNDEA) is used to construct a model that applies to three different activities: harbor management, stevedoring and warehousing operations. We will further divide each activity into two process types, production processes and services processes. We will also adopt a Delphi survey approach and use the Analytic Network Process (ANP) to identify these processes’influence dependence and their degree of importance for the MNDEA model setting. An empirical application demonstrates the performance of Taiwanese container ports by using MNDEA with window analysis techniques via the directional distance functionThe results demonstrate that the application is effective in indicating and/or suggesting resource-adjustments, while considering which undesirable output levels and shared inputs were involved. The results also present directions for possible improvements in workplace efficiency.
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Thi Quynh Mai Pham, Gyei Kark Park and Kyoung-Hoon Choi
The purpose of this paper is to present an integrated model to measure the operational efficiency of the top 40 container ports in the world for a five-year continuous period…
Abstract
Purpose
The purpose of this paper is to present an integrated model to measure the operational efficiency of the top 40 container ports in the world for a five-year continuous period using a two-stage uncertainty data envelopment analysis (UDEA) combined with fuzzy C-means clustering method (FCM).
Design/methodology/approach
UDEA model is adopted for measuring the efficiency of container ports to overcome the limitation of the basic model, which is unable to handle uncertain data that are easy to meet in practice. FCM algorithm is implemented to find similar distribution efficiency scores of two stages and the cluster similar efficiency scores of container ports into various groups.
Findings
The combination of the two-stage UDEA model and the FCM algorithm provided a more comprehensive view when evaluating the performance of container ports. The UDEA results show that most of the container ports have reduced their profitability level in the second stage and most of the efficient container ports have turned into inefficient ones because of their small scale.
Originality/value
This paper proposes using the two-stage UDEA model to evaluate port efficiency based on two main aspects of productivity and profitability. Moreover, it combines DEA and FCM algorithms to offer a more comprehensive view when measuring the performance of container ports.
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Patrik Jonsson, Johan Öhlin, Hafez Shurrab, Johan Bystedt, Azam Sheikh Muhammad and Vilhelm Verendel
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Abstract
Purpose
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Design/methodology/approach
A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.
Findings
The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.
Practical implications
The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.
Originality/value
The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?
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