Analysis of a Train-operating Company’s Customer Service System during Disruptions:Conceptual Requirements for Gamifying Frontline Staff Development

This paper provides an account of an action research study into the systemic success factors which help frontline staff react to and recover from a rail service disruption. This study focuses on the effective use of information during a disruption to improve customer service, as this is a priority area for train-operating companies (TOCs) in Great Britain. A novel type of systems thinking, known as Process-Oriented Holonic Modelling (PrOH), has been used to investigate and model the ‘Passenger Information During Disruption’ (PIDD) system. This paper presents conceptual requirements for a gamified learning environment; it describes ‘what’; ‘how’ and ‘when’ these systemic success factors could be gamified using a popular disruption management reference framework known as the Mitigate, Prepare, React and Recover (MPRR) framework. This paper will interest managers of and researchers into customer service system disruptions, as well as those wishing to develop new gamified learning environments to improve customer service systems

Supply Chain Disruption Costs Study in International Containerised Maritime Transportation

The global economy relies highly on international trade, and the international maritime transport system acts as the lifeblood carrying and transporting materials and goods globally, realizing the economy globalization in an effective and efficient way. However, globalization increases the interdependence and complexity of global supply chains and drives it to be more vulnerable to disruptions. Meanwhile, the international marine transport system is a complex and intertwined system exposed to high risks and decreased safety due to its very accessibility and operational flexibility. Thereby, global supply chains integrated with international maritime transportation systems are inherently vulnerable to various disruptions. Studies of supply chain disruptions particularly quantifying transport related disruption costs are becoming increasingly important. However, research on maritime transport related supply chain disruptions, in particular, quantifying its disruption costs is under-represented in the transport literature, due largely to the features of supply chain disruptions, but also because of the complexity of maritime related supply chains. Current research in transportation has tended to concentrate on shippers’ transport mode choice and port selection. In the context of a global market, however, the behaviour of maritime containerised shippers has to be viewed as a complex decision and an integral element of the supply chain management strategy. Those shippers’ transportation choice decisions should be emphasized and studied to reveal their behaviour changes between normal operations and disruption circumstance. This research adds to the paucity work on investigating the maritime transport related supply chain disruptions and quantifying its disruption costs based on shippers’ maritime transportation choice behaviour. It presents the results of a microanalysis of freight transport choice decisions in an international containerised maritime transport chain context. The Latent Class Model (LCM) is applied to identify the key service attributes and its preference heterogeneity in maritime transportation and to estimate the marginal values for the quality of maritime transport service with and without a disruption, simultaneously, quantifying the disruption costs through comparing each attribute’s marginal value difference between normal and disruption operations. The Seemingly Unrelated Regression model (SURE) is utilized to explore the sources influencing shippers’ preference heterogeneities. In doing so, we are able to gain an understanding as to where and how much should be invested in order to facilitate recovery in the case of a disruption based on the view of the maritime participants’ perspectives. The research results confirm freight rate, transit time, reliability, damage rate, and frequency as the key service attributes influencing shippers’ transport choice. They also reveal shippers’ VOT increase by more than four-times, VOR nearly double, and VOD increase about twenty percent if a disruption takes place, and identify shippers’ transport decisions vary with its product, shipment, company and supply chain characteristics no matter with or without a disruption. This research quantifies the costs of supply chain disruption in containerised maritime transport context for the first time, and its results provide useful industrial implications for maritime transport chain related parties