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Energy groups are cargo owners with large amounts of energy sources (such as coal) to transport. To achieve a satisfactory tradeoff between the reliability requirements of the sea transportation process and the need to control the investment cost, they usually set up a self-owned fleet supplemented by a chartered fleet. This paper aims to investigate the best fleet structure and to evaluate the investment scheme under volatile circumstances in the shipping market.

The authors construct a mathematical model to determine the ratio of the self-owned fleet to the total fleet to minimize fleet operating costs. The volatility of both freight rates and oil prices is taken into consideration. The CPLEX solver is used to empirically analyze real data from an energy group in China, and the ship investment plan is evaluated considering the technical and economic feasibility.

If the ratio of the self-owned fleet to the total fleet is increased to the optimal of 90.40%, the total operating cost is reduced by 33.98%. Thus, the energy group should increase its capacity with a Panamax vessel of approximately 82,000 DWT. Purchasing a 5-year-old secondhand ship and building a new ship both have good investment return indicators.

For cargo owners engaging in transporting bulk cargo domestically in China, the suggested fleet ratio can provide a reference with a universal application scale, given the boundary economic conditions (including the volatility of freight rates and oil prices in the shipping market) in the paper.

The learning outcomes of this case study are to understand the business model canvas and value propositions and apply advanced business innovation tools in electric vehicle business models; evaluate the current cargo vehicle scenarios at national and global levels and draw out the possibilities and costs for a new player; extrapolate the future scenario of the cargo economy, its electrification and positioning in a business-to-business (B2B) and business-to-customer (B2C) segment, especially for a developing economy; and improve the student’s ability to get organisational buy-in and execute new business models.

LoadExx is a fully electrified electric cargo service focusing on logistics in Kolkata, a metropolitan city in the eastern part of the country. The service of LoadExx commenced in January 2021 in the B2B segment after overcoming its then issues of driver hesitancy and customer anxiety and financial issues to adopt electrified cargo systems. The conundrum faced by LoadExx in its commencement thus had been solved under the able guidance of its owner Amit Arora. The case study was positioned four months after the commencement of LoadExx. To gain market power and traction, Arora and his team came up with the idea of market expansion. However, the current conundrum was whether LoadExx would enter the B2C segment in its current location or expand with the same business model to other parts of the country. The expansion was to be implemented in the immediate future to retain its rarity and reduce the imitability of the business model of LoadExx. This case study details the logistics and market operations of the cargo sector, especially electric cargo, in a developing economy, especially India. A teaching note supplementing the “Cracking the conundrum of e-cargo logistics: curious case of LoadExx” case study has been provided.

This case study is designed for undergraduate and postgraduate students and senior management professionals in executive education programmes undertaking courses in logistics management and supply chain operations and related cargo logistics courses. This case study denotes integrating key processes from end-users and gaining the trust of drivers, thereby showing the perspective of the plight and conundrums of a cargo aggregator working in the B2C segment. This case study could be used to discuss concepts related to not-for-profit firms, aggregators, policymakers and think tanks.

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

This paper aims to study the implication of the stochastic gross-profit-per-day objective on the ship profitability and the ship capacity and speed.

The paper has used the mathematical model and the solution methodology given by El Noshokaty, 2013, 2014, 2017a, 2017b, and SOS, 2019.

The paper finds that if the ship owner follows the rate concept and the cargo demand forecast, he can improve the profitability of his company and be able to select the proper capacities and speeds for the ships used.

The findings are not only useful for the shipping or other cargo transport companies but also for businesses like gas reservoir development, car assembly lines in the industry, cooperative farming and crop harvesting in agriculture, port cargo handling in trade and road paving in construction.

The contribution of this paper lies in notifying the ship owners of the possible profitability improvement and the consequences of building ships of larger capacities and slower speeds.

The purpose of this paper is to resolve three problems in ship routing and scheduling systems. Problem 1 is the anticipation of the future cargo transport demand when the shipping models are stochastic based on this demand. Problem 2 is the capacity of these models in processing large number of ships and cargoes within a reasonable time. Problem 3 is the viability of tramp shipping when it comes to real problems.

A commodity-trade forecasting system is developed, an information technology platform is designed and new shipping elements are added to the models to resolve tramp problems of en-route ship bunkering, low-tide port calls and hold-cleaning cost caused by carrying incompatible cargoes.

More realistic stochastic cargo quantity and freight can now be anticipated, larger number of ships and cargoes are now processed in time and shipping systems are becoming more viable.

More support goes to ship owners to make better shipping decisions.

New norms are established in forecasting, upscaling and viability in ship routing and scheduling systems.

Cargo loss has been a major issue in logistics management. However, few studies have tackled the issue of cargo loss severity via business analytics. Hence, the purpose of this paper is to provide guidance about how to retrieve valuable information from logistics data and to develop cargo loss mitigation strategies for logistics risk management.

This study proposes a research design of business analytics to scrutinize the causes of cargo loss severity.

The empirical results of the decision tree analytics reveal that transit types, product categories, and shipping destinations are key factors behind cargo loss severity. Furthermore, strategies for cargo loss prevention were developed.

The proposed framework of cargo loss analytics provides a research foundation for logistics risk management.

Companies with logistics data can utilize the proposed business analytics to identify cargo loss factors, while companies without logistics data can employ the proposed cargo loss mitigation strategies in their logistics systems.

This pioneer empirical study scrutinizes the critical cargo loss issues of cargo damage, cargo theft, and cargo liability insurance through exploiting real cargo loss data.

This paper investigates the announcement effect of shipping sale-and-leaseback (SLB) transactions. As an emerging source of financing, a growing deal of interest has been paid to the SLB. However, little is known about a variety of aspects of SLB transactions in the shipping industry. In this regard, this study examines the stock market reaction to the SLB announcements of shipping firms and their impact on shareholders' wealth.

A sample of 15 shipping SLB deals commenced by publicly listed Korean shipping companies during 2009–2023 are examined in this research. The announcement effect is measured by abnormal returns (AR) of their stocks based on the event study analysis.

It is found that the AR on the shipping SLB announcement date is, on average, −0.84% while there is no statistical significance. However, the results indicate that shareholders of shipping companies engaging in large-sized SLBs can experience positive AR around the announcement date.

This study is the first attempt to investigate the announcement effect of SLB transactions on the shipping industry and their impact on shareholders' wealth. The findings in this research can offer implications for the financing decisions of shipping companies and investment decisions of stock investors.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

This research proposes a framework to conceptualise the potential realm of data regarding shipping connectivity for application of data analytics which can be used to generate deeper insights with respect to the state of such linkages and potential areas for practical application.

The study method involved comprehensive presentation of different perspectives of assessing shipping connectivity and levels of data contained within container shipping services and proposed potential application to analyse profitability, performance, competitiveness, risk and environmental impact.

Advances in capabilities to handle large volumes of data offer scope for an integrated approach which utilises all available data from various stakeholders in analyses of liner shipping connectivity. Research shows how different types of data contained in container shipping services are related and can be organised for application of data analytics.

Research implications are offered to shipping lines, port managers and operators and policymakers.

This research presented a conceptual framework that captures the range of data involved in container shipping services and how data analytics can be practically applied in an integrated manner.

This paper is the first in literature to discuss in detail the different levels of data that reside within shipping services that constitute liner shipping connectivity for application of data analytics.