A web mobile application for agricultural machinery cost analysis

Machinery cost is the major cost item in farm businesses in highly mechanized production systems. Moreover, in the last years, high power machines, advanced technologies, higher cost for spare parts and repairing, and fuel consumption contributed to an even more higher increase of the machinery costs. Many engineering and economic methodological approaches have been implemented to calculate machinery use and cost, but they are almost confined in scientific and technical documentations making it difficult for a farmer to apply these approaches for deciding on buying, leasing, or sharing agricultural machinery. Information and communications technology (ICT) has an increasingly important role on business processes and provides a powerful foundation to address many daily problems. Today users want to be connected to useful information in real time. To that effect, the aim of this work was to develop an easy-to-use mobile application, called “AMACA” (Agricultural Machine App Cost Analysis) for determining the machinery cost in different field operations and making it available via a web mobile application using a cross-platform approach. The customer-driven Quality Function Deployment [QFD] approach was implemented in order to link the user expectations with the design characteristics of the app. The AMACA app is free, readily available, and does not require any installation on the end user's device. It is a cross-platform application meaning that it operates on any device through a web interface and is supported by various browsers. The user can make subsequent calculations by varying the input parameters (fuel price, interest rate, field capacity, tractor power, etc.) and compare the results in a sensitivity analysis basis. AMACA app can support the decisions on whether to purchase a new equipment/tractor (strategic level), the use of own machinery or to hire a service, and also to select the economical appropriate cultivation system (tactical level). © 2016 Elsevier B.V.