THE REAL OPTIONS PUZZLE FOR MICHIGAN TART CHERRY PRODUCERS

Capital budgeting decisions faced by tart cherry producers often challenge our traditional valuation techniques. Real Options Valuation (ROV) methods may be useful but assumptions of existing ROV approaches are restrictive and, in some cases, unrealistic. In this paper we assert that use of existing option pricing methods can not be justified. Instead, dynamic programming approach is more appropriate. We develop a multi-period model and use it to obtain an optimal orchard replacement policy. The model is applied to an example farm from Northwestern Michigan and the results provide the following messages. First, flexibility options can be estimated for individual tart cherry producers using the DP approach albeit, indirectly. Second, a farmer who uses the DP approach to develop contingency optimal replacement rules will be better off than one who uses an ad hoc standard replacement rule. Third, if the SW climate scenario shifts to NW Michigan, tart cherry orchard values may fall substantially with implications on the future of tart cherry production in that region, unless compensating price increases follow.Farm Management,

Fiber-optic interferometric sensor for monitoring automobile and rail traffic

This article describes a fiber-optic interferometric sensor and measuring scheme including input-output components for traffic density monitoring. The proposed measuring system is based on the interference in optical fibers. The sensor, based on the Mach-Zehnder interferometer, is constructed to detect vibration and acoustic responses caused by vehicles moving around the sensor. The presented solution is based on the use of single-mode optical fibers (G.652.D and G.653) with wavelength of 1550 nm and laser source with output power of 1 mW. The benefit of this solution lies in electromagnetic interference immunity and simple implementation because the sensor does not need to be installed destructively into the roadway and railroad tracks. The measuring system was tested in real traffic and is characterized by detection success of 99.27% in the case of automotive traffic and 100% in the case of rail traffic.Web of Science2662995298