In this video, Agnieszka Nowinska (Aalborg University Business School) and Hans-Joachim Schramm (Copenhagen Business School) talk about their research on chartering during the financial crisis in container shipping. The session has been developed in collaboration with MARLOG.
This study presents a novel approach to forecast freight rates in container shipping by integrating soft facts in the form of measures originating from surveys among practitioners asked about their sentiment, confidence or perception about present and future market development. As a base case, an autoregressive integrated moving average (ARIMA) model was used and compared the results with multivariate modelling frameworks that could integrate exogenous variables, that is, ARIMAX and Vector Autoregressive (VAR). We find that incorporating the Logistics Confidence Index (LCI) provided by Transport Intelligence into the ARIMAX model improves forecast performance greatly. Hence, a sampling of sentiments, perceptions and/or confidence from a panel of practitioners active in the maritime shipping market contributes to an improved predictive power, even when compared to models that integrate hard facts in the sense of factual data collected by official statistical sources. While investigating the Far East to Northern Europe trade route only, we believe that the proposed approach of integrating such judgements by practitioners can improve forecast performance for other trade routes and shipping markets, too, and probably allows detection of market changes and/or economic development notably earlier than factual data available at that time.
This chapter is a historical case study of Maersk Line, the world’s leading container carrier. Maersk Line’s global leadership was achieved within a relatively short time period and was the result of Mærsk Mc-Kinney Møllers decision in 1973 to enter container shipping—the biggest investment in the history of the AP Moller companies. When Maersk Line managed to achieve global leadership in a period of just about 25 years, the company’s own country offices were particularly important. They allowed the interconnection of three types of networks: The physical network of ships and routes, the digital network of information and communication systems and the human network of Maersk employees. The interaction between the vessels, the systems and the people is still at the core of the company today and central to its continued development.
The literature on liner shipping includes many models on containership speed optimization, fleet deployment, fleet size and mix, network design and other problem variants and combinations. Many of these models, and in fact most models at the tactical planning level, assume a fixed revenue for the ship operator and as a result they typically minimize costs. This treatment does not capture a fundamental characteristic of shipping market behavior, that ships tend to speed up in periods of high freight rates and slow down in depressed market conditions. This paper develops a simple model for a fixed route scenario which, among other things, incorporates the influence of freight rates, along with that of fuel prices and cargo inventory costs into the overall decision process. The objective to be maximized is the line’s average daily profit. Departing from convention, the model is also able to consider flexible service frequencies, to be selected from a broader set than the standard assumption of one call per week. It is shown that this may lead to better solutions and that the cost of forcing a fixed frequency can be significant. Such cost is attributed either to additional fuel cost if the fleet is forced to sail faster to accommodate a frequency that is higher than the optimal one, or to lost income if the opposite is the case. The impact of the line’s decisions on CO2 emissions is also examined and illustrative runs of the model are made on three existing services.
Maersk Line er verdens førende containerrederi og blandt de mest betydningsfulde virksomheder i Danmark. Den globale førerposition blev opnået på relativt kort tid og var et resultat af rederiets beslutning i 1973 om at gå helhjertet ind i containerskibsfarten. Beslutningen blev startskuddet til Maersk Lines dybe internationalisering, hvor rederiet ændrede sig fra at være en overvejende danske virksomhed, der betjente internationale markeder, til at være en genuin transnational virksomhed. Med fokus på opbygningen af Maersk Lines globale organisation og særligt etableringen af egne kontorer i udlandet indkredses rederiets tilpasning og udvikling i perioden fra 1973-1999.
Container shipping is generally considered a global business. This truth may not hold from a single-company perspective. The companies’ physical operation networks show that container carriers operate differently and follow different paths in their internationalisation development. Additionally, the degree of internationalisation, measured on the basis of sea-oriented operations, differs from that measured according to land-oriented front-end marketing and sales activities. The purpose of this study is to further examine the internationalisation patterns of shipping lines. An examination of the front-end activities and the structures of leading container-shipping companies is conducted. The sales office networks of the sector’s 20 largest companies worldwide (by twenty-foot equivalent unit capacity) are analysed as key indicators. The numbers of sales offices are measured by analysing the websites of the sample (20 companies), as well as annual reports and other publicly available data sources. The findings show that not all shipping companies are international, by virtue of the industry. While it is difficult to observe differences in the overall patterns of the sales networks at a macro level, some companies differ in their activities. The data set also shows that market share and total capacity are not necessarily good indicators of a carrier’s worldwide presence. This research is based on secondary data. Other important transactional and market-oriented considerations should be examined before drawing conclusions about the internationalisation of container-shipping companies and of the industry. This paper contributes to the relevant existing research, particularly by adding its view on the demand-oriented criteria as suggested by Dunning and Lundan (2008).
This study introduces a state-of-the-art volatility forecasting method for container shipping freight rates. Over the last decade, the container shipping industry has become very unpredictable. The demolition of the shipping conferences system in 2008 for all trades calling a port in the European Union (EU) and the global financial crisis in 2009 have affected the container shipping freight market adversely towards a depressive and non-stable market environment with heavily fluctuating freight rate movements. At the same time, the approaches of forecasting container freight rates using econometric and time series modelling have been rather limited. Therefore, in this paper, we discuss contemporary container freight rate dynamics in an attempt to forecast for the Far East to Northern Europe trade lane. Methodology-wise, we employ autoregressive integrated moving average (ARIMA) as well as the combination of ARIMA and autoregressive conditional heteroscedasticity (ARCH) model, which we call ARIMARCH. We observe that ARIMARCH model provides comparatively better results than the existing freight rate forecasting models while performing short-term forecasts on a weekly as well as monthly level. We also observe remarkable influence of recurrent general rate increases on the container freight rate volatility.
We introduce a decision support tool for liner shipping companies to optimally determine the sailing speed and needed fleet for a global network. As a novelty we incorporate cargo routing decisions with tight transit time restrictions on each container such that we get a realistic picture of the utilization of the network. Furthermore, we show that it is possible to extend the model to include optimal time scheduling decisions such that the time associated with transshipments is also reflected accurately. To solve the speed optimization problem we propose an exact algorithm based on Benders decomposition and column generation that exploits the separability of the problem. Computational results show that the method is applicable to liner shipping networks of realistic size and that it is important to incorporate cargo routing decisions when optimizing speed.