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This chapter explains the impact containerisation has on the various partners of the global supply chain and the challenges companies encounter and the solutions they use in dealing with empty container repositioning.

The phenomenon of imbalanced container flows and its impact on shipping lines, shippers, container haulage companies, port development and the economy are presented. Special attention is given to explain the many solutions companies use to reduce the impact of empty container repositioning, hence tracing out the past research that led to these solutions and pointing to potentially new research directions in the future.

Because of the widespread use of containerisation and the imbalanced container flows that results from globalisation, empty container repositioning will be an ongoing issue for the maritime logistics industry. Many solutions are being used, but there is room for improvement and more research is needed.

Empty container repositioning is an important issue but has not been deemed as such in the literature. This chapter explains the reasons it is important and that its impact is not limited to shipping lines only but affects the whole supply chain.

Purpose: Technological innovations and frameworks that provide a framework for unification have evolved to improve information exchange across organisational units and information security. These integration technologies share and communicate information using defined protocols and different data. Service-oriented architecture (SOA) is a significant emerging approach that enables modular design solution construction.

Methodology: These designs are beneficial when many apps operating on different architectures and networks need to connect. A well-defined strategy and company-specific guidelines are essential for ensuring the firm’s systematic adoption of such an architecture. The critical components of MASSOASCM ‘(Multi-Agent System Service Oriented Architecture Supply Chain Management’ are a multi-agent system (MAS), a service-oriented structure, and supplier management. The MASSOASCM model has been made, and a production unit has been made to show how it works.

Findings: It has been stated that it saves development costs, and inventory management, all of which are critical concerns in any company. Our goal is to create an inventory control approach that relies on MAS and SOA but also a simulation that demonstrates how it works and may enhance Supply Chain Management (SCM) productivity in a production plant.

Practical Implications: The SCM implementation comprises three different services: SCM, SOA, and MAS. These facilities are constructed, maintained, planned, and implemented individually before being brought together collectively using MAS and SOA techniques.

When forecasting intermittent demand the method derived by Croston (1972) is often cited. Previous research favorably compared Croston's forecasting method for demand with simple exponential smoothing assuming a nonzero demand occurs as a Bernoulli process with a constant probability. In practice, however, the assumption of a constant probability for the occurrence of nonzero demand is often violated. This research investigates Croston's method under violation of the assumption of a constant probability of nonzero demand. In a simulation study, forecasts derived using single exponential smoothing (SES) are compared to forecasts using a modification of Croston's method utilizing double exponential smoothing to forecast the time between nonzero demands assuming a normal distribution for demand size with different standard deviation levels. This methodology may be applicable to forecasting intermittent demand at the beginning or end of a product's life cycle.