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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.

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.

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.

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.

Supply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.

The proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.

The findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.

There are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.

1. Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

2. Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

3. Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

4. Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Since the 2010s, market conditions for container shipping companies have been deteriorating owing to decreasing container cargo trade and increasing supply capacity. This study aims to contribute to the empirical literature on the container shipping industry market structure. Specifically, this study aims to investigate the extent of market competition.

This study analyzes the market structure and evaluates the market power of shipping companies through a non-structural test.

The H-statistic for the entire period of 2004–2018 was 0.37, which is significantly different from zero. This indicates the absence of monopoly pricing throughout the entire period. For the time-phased estimates, the H-statistic between 2004 and 2008 is 0.15, which is not significantly different from zero. On the other hand, the H-statistic from 2009 to 2018 was 0.40, which differs significantly from zero.

As the Far East Freight Conference had released tariffs and charge rates by item for container shipping routes, monopolistic pricing is said to have appeared until the European Union abolished the European Economic Community (No. 4056/86) in 2008, before the economic crisis. However, this study indicates that pricing in the container shipping industry has been distinctly non-monopolistic; further, competition seems to have intensified since 2008. Industry competitiveness is of interest not only to academics but also to practitioners, including policymakers, especially when considering competition policies.

In this paper, we present a proposed information environment (PROPIE) for enhanced interaction and value‐adding of electronic documents (e‐documents). The design of PROPIE was based on a thorough user needs and requirements assessment in interacting with information through well‐documented findings, and a focus group with twelve participants to elicit features that were deemed desirable in future interactions. The design was also based on an earlier work which reviewed the advancements in various user interface (UI) technologies, visualisation and interactive techniques, and a consideration of novel information structuring and organisation techniques that pose important implications for the design of more advanced UIs. Providing a suite of novel features and interactive tools that can be flexibly combined, PROPIE allows users to apply multiple novel ways to query intuitively and navigate information in an e‐document. The querying and browsing processes in PROPIE are supported by various interactive and visualisation techniques. Users work within a visually sovereign, integrated environment for information gathering and organising, based on navigable, fractional information objects that are also affiliated with rich metadata and additional layers of value‐adding information. A set of interface mock‐ups was developed to demonstrate the potential of the environment in supporting the design of a new generation of electronic journals (e‐journals). We report here empirical results from a study conducted to obtain representative users‘ feedback with regard to using PROPIE for interacting with e‐journals. Twenty‐two participants from a variety of academic backgrounds participated in the evaluation. Overall, PROPIE was found to have the potential both for enhancing the user’s interaction with information captured within e‐journals and for adding value to e‐documents in various ways.

The purpose of this paper is to understand and explain how firms use simulation-based decision support systems (DSSs) to optimize container space utilization.

Using a case study of a logistics company, this research analyzed the application of optimization software through simulation to make efficient loading decisions. The current study attempted to find a method for optimizing and making a loading plan to achieve higher container space utilization using a simulation method.

A simulation-based DSS and application of an optimization method contributes to the reduction of container shipment volume, and saves logistic costs and its delivery time. This research offers a method for optimizing a loading decision to optimize container space utilization.

The present study is based on a single case study of only one specific type of product, i.e., motorcycle spares parts within a specific industry.

Apart from adding value to the shipment process and improving the efficiency of loading plans, with the use of optimization software, the collaboration between buyers and suppliers can be encouraged to reduce response time and bringing transparency in the pricing process of the shipment.

This research addresses a key concern in the transportation industry: how to reduce the logistics costs and the delivery time. This study demonstrates how a simulation-based tool can be used to reduce freight cost, cycle time, instill waste minimization and improve overall value addition.

The learning outcomes are as follows: to analyse the issue(s) presented within specific case study context (C4); to formulate solutions to identified issue(s) within specific case study context (C5); and to synthesise a group plan to solve issue(s) within specific case study context (A4).

In 2017, China proclaimed that it would no longer accept plastic waste for recycling, this was in-line with China’s Operation “National Sword” to review the quality of these plastic imports to ensure their recyclability. This sent shock waves through a now globalised recycling network, with China previously having imported 95% of the EUs and 70% of US plastics that had been collected for recycling. This plastic backlog was then diverted to South-East Asian nations, particularly Malaysia, which this case focuses the discussion upon. While the potential for significant economic benefits drew the attention of illegitimate and unscrupulous businessmen alike, the environmental degradation from the often, low technological recycling processes and even burning of low-grade plastics brought profound negative impacts. This case focuses upon, then Minister, Yeo Bee Yin who led the Ministry of Energy, Science, Technology, Environment and Climate Change, in which she took an active and aggressive stance in attempt to stop Malaysia becoming the dumping ground for the global plastic crisis.

This case is appropriate for final year undergraduate and any postgraduate degrees in Business.

Teaching notes are available for educators only.

CSS 4: Environmental Management.

India should hold a privileged position in maritime transportation due to its extensive coastline and advantageous location. However, the country heavily relies on other maritime nations like Singapore and Colombo for transshipment due to insufficient infrastructure and policy framework, and this has created disadvantage to Indian goods in the international market. The government has launched a significant drive to promote three transshipment ports in southern India with top-notch amenities in response to this worrying circumstance. It is anticipated that these ports would compete with the existing transshipment ports, particularly with Colombo, and divert the transshipped goods back to India. The move is expected to make Indian exports more competitive besides making India less prone to geopolitical and economic disturbances in the region. However, these initiatives have been met with many challenges. In fact, the first attempt of the Indian government to set up an International Container Transshipment Terminal (ICTT) at Vallarpadam in Cochin Port has met with failure despite its best infrastructure and connectivity. High-cost structure seems to deter the competitiveness of this port. Furthermore, the development of Vizhinjam into a transshipment hub in the same region has put additional pressure on Vallarpadam. This chapter draws attention to certain factors that might be considered to enhance the competitiveness of Cochin Port. Also, the study highlights the snags that could have well been avoided while implementing the project and might as well be avoided while implementing other projects in line.

This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.

The research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.

Validation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.

The main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

This study aims to use a thermal elastohydrodynamic lubrication (EHL) algorithm incorporating an Eyring flow model to solve a steady-state contact in simple sliding motion.

A theoretical model was used to investigate the effect of starvation on the surface dimple phenomenon by gradually reducing the thickness of the inlet oil layer.

The increase in the starvation degree reduces the dimple depth, film thickness, the pressure peak and the temperature rise. Under the severe starvation condition, the dimple is eliminated so that the EHL contact becomes partly parched. In elliptical results, for the same starvation parameters, the oil replenishment is stronger than that in circular contact.

This paper fulfils an exploration to study how the oil starvation influences the surface dimple phenomenon.

The paper discusses six Japanese marketing cases in depth. It is shown how the “success” interpretation which so often is promulgated by the firms and press alike in fact hides serious mistakes and results which in other countries would be interpreted as “failures”.