DEMAND FORECASTING IN THE MARITIME INDUSTRY, A CASE OF MAERSKLINE GHANA
DOI:
https://doi.org/10.14738/abr.41.1841Abstract
Demand forecasting is of critical essence to the maritime industry, especially in Ghana. On this note the study sought to achieve among other things by identifying the type(s) of model(s) used by Maritime industry in forecasting their operational demands as well as develop an appropriate forecasting model(s) for these industry using Maersk line as a case study. We realized that Maersk line preferred to be responsive and as such incur more cost by underutilizing their capacity. Maersk line Ghana should not use only one model to forecast for both exports and import data. We therefore recommend from our study that the organization should use exponential smoothing model of forecasting to forecast their export data only.
References
Corbett, J. J., and J. J. Winebrake (2007), Sustainable Movement of Goods: Energy and Environmental Implications of Trucks, Trains, Ships, and Planes, Environmental Management, November.
The Impacts of Globalisation on International Maritime Transport Activity (2008). Global Forum on Transport and Environment in a Globalising World 10-12 November 2008, Guadalajara, Mexico
Juma, K. (The Impact of Inventory Management and Performance of Private Organizations in Uganda. A Case Study of Coca- Cola Mbarara Plant in Mbarara Municipality
Chendroyaperumal, C. (2009). DEMAND FORECASTING TECHNIQUES: AN EVALUATION. National Institute of Management Studies. Retrieved March 30, 2015, from www.researchgate.net.
Det Norske Veritas (DNV) (2004). Corporate Social Responsibility and the Shipping Industry, Project Report, No 2004-1535, Revision No1
Duell, T. (2001). Forecasting Demand in a Changing Economy, A Formulations Pro, Inc. White Paper, pages 4-8.
Gardner Jr., E. S. (2006). Exponential smoothing: The state of the art Part II. International Journal of Forecasting, 22, 637-666.
Gardner Jr., E.S. & McKenzie, E. (1985) Forecasting trends in time series, Management
Science, 31, 1237-1246.
Hope, C. A. and Muhlemann, A. P., (1997) Service Operations Management: Strategy, Design and Delivery, Prentice Hall, Hemel Hempstead, 352pp.
Huang Y. and Lee, Y. (2011). Accurately Forecasting Model for the Stochastic Volatility Data in Tourism Demand, Scientific Research, An Academic Publisher, Vol.2 No.5, November 2011
Jacobs,R.F. and Chase, B. R., (2008). Operations and supply management: the core, Book, McGraw-Hill/Irwin series operations and decision sciences
Kumar, S., and J. Hoffmann (2002), Chapter 3 Globalization: the Maritime Nexus, in
Handbook of Maritime Economics and Business, pp. 35-62, Informa, Lloyds List Press, London
Korpela, J. and M. Tuominen, 1996. “Inventory Forecasting With a Multiple Criteria Decision Tool.” International Journal of Production Economics, 45: 159-168.
Krumwiede, D.W. & Sheu, C.* (2002). A model of reverse logistics entry by third-party providers, Omega, 30(5), 325-333.
Magirou V., Psaraftis, H. and Christodoulakis, N., (1992), Quantitative Methods in
Shipping: A Survey of Current Use and Future Trends, Report No. E115, Center for Economic Research, Athens University of Economics and Business.
Nurrahman, A., (2012). Definition of Demand Forecasting, Article BlogNotions
Phelan, M. and McGarraghy, S., (2006) Clustering & Demand Forecasting in Telecommunications Supply Chains 3rd CEMS Research Seminar 2006 SUPPLY CHAIN MANAGEMENT: THE CHALLENGE OF OUTSOURCING & OFFSHORING SUPPLY CHAIN ACTIVITIES Riezlern, Austria, , 25-JAN-06 - 29-JAN-06
Progoulaki M., 2005, "Strategic Management of Multicultural Shipping Crews: choice of research methodology", 12th Panhellenic Undergraduate Intensive Seminar- Conference for Doctoral Students (Anogia Summer Schools): Methodological Issues of Research in Social Sciences, Rethymno, Crete, Greece, November 18-21.
Rodrigue, J.P.(2010). Maritime Transportation: Drivers for the Shipping and Port Industries, Forum Papers, International Transport Forum 2010 Transport and Innovation Unleashing the Potential
Sletmo, G. K. (1989) Shipping’s Fourth Wave: Ship Management and Vernon’s trade cycles, Maritime Policy and Management 16 (4), pp. 293-303
Tseng, Y., W.L. Yue and M.A.P. Taylor, 2005. The role of transportation in logistics chain, 5: 1657-1672.
Turban, et al., (2007). Deision Support Systems and Intelligent Systems, 7th edition, pp 816-828 Prentice-Hall of India
Yin, R.K., 2003. “Case Study Research: Design and Methods: (Applied Social Research Methods, Volume 5)” SAGE Publications, Inc; Third Edition edition Newbury Park, Calif.: Sage. ISBN-13: 978-0761925538
