Intermodal transport has undoubtedly become a reflection of the technical, technological, and organizational progress taking place in general cargo transport. It is simultaneously a goal and a tool for those performing and organizing the transport process. Due to its complexity and multifaceted nature, the phenomenon of intermodal transport requires appropriate management, which is closely linked to marketing. The logic of marketing assumes the forward-looking nature of data used in decision-making processes. Therefore, modeling and forecasting the dynamics of processes for introducing a new service to the market is the subject of research into the demand for this service. However, under conditions of uncertainty, building economic models of a given service, connecting the past and the present with a hypothetical future, is an extremely difficult task.
Forecasting theory contains about 200 different methods and their modifications. Each of these methods is useful only in specific situations. In the available literature on the subject, there is a lack of uniform, scientific criteria for selecting a forecasting method for a real process in a specific situation. Therefore, forecasting remains an art, despite the existence of a rich mathematical and statistical apparatus. The main reason for the failure of research conducted in this area is the lack of a systemic approach to describing the structural core of the marketing subsystem in a transport company, and the mutual relationships between the elements of the modeled service and its evolution over time. The authors’ intention was to develop a comprehensive approach to assessing the competitiveness of a company organizing intermodal transport, based on marketing activities.
Forecasting the effectiveness of using intermodal transport
<\/strong>The goal of marketing research is to show the possibilities for a company to occupy a competitive position in the market while satisfying the demand for transport and meeting customer requirements. The main task of this research is to determine the conditions for obtaining optimal relationships between supply and demand in the transport services market. From the analysis of supply and demand, one can draw conclusions about the possibilities of carrying out transport and the trends in the development of demand in the future. Research into the transport services market also concerns transport companies operating in this market, their position, and the transport technologies used. In strategic planning, the following marketing activities can be used: the Ansoff product-market matrix, the growth matrix developed by the Boston Consulting Group, and the multi-factor portfolio matrix introduced by General Electric. The activities mentioned above can be used at various stages of a company’s business planning. In the case of transport companies, strategic planning should additionally be based on information about the volume and conditions of transport, carriers, and cargo recipients.
The marketing research model proposed below takes into account the following variable factors: <\/p>
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service typology<\/div>
<\/li>shipper classification<\/div>
<\/li>cargo group consistency.<\/div>
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<\/ul>Intermodal transport, as a new service, is presented in the form of a dynamic graph of variable factors with vertices with special numbering. Each vertex is assigned a number depending on the level of the factor it represents. The first level maps the typology of recipients, the second level maps the types of services, the third level maps the components of services, and the fourth level maps the characteristics of services. The vertices of the graph are connected by edges. The whole constitutes a four-level hierarchical structure, which is described by binary matrices associated with the given graph.
Each vertex of the first, second, and fourth level is assigned a weight that changes over time. The weight contains expert information about the distribution of profit and risk, supply and demand among different classes of recipients, presented in the form of a matrix.<\/p>The article comes from the journal “Logistyka” 2/2011.<\/p>