Adoption is slow and extremely unprofitable.

Researchers have puzzled over the slow adoption of precision agriculture by small-scale farmers. By recording the decision paths such farmers have to make along the implementation process of deploying for the first time site-specific fertilization, it was possible to show, using a prototypical small farm model, that farms with outdated, non-retrofittable technology are effectively excluded from digitization, as it will never be profitable over the lifetime of the precision technology. This results primarily from the high financial outlay for new equipment, and far less from the working time required for implementation.

Furthermore, it became evident that even when retrofittable mechanization is available, the investment is at the limit of a profitable use at the current costs and the model farm size. If a farm already uses digital technology that can be used for precision agricultural management at modest cost, or if a farm contracts out the site-specific fertilization program, then a positive linear effect in the operational result can be observed, delivering from 151.33 to 192.17 € ha−1 of accumulated added revenue at the end of useful technology life.

Most importantly, it was shown that under uncertainty, inefficiency of site-specific fertilization, and non-linear behavior in the aggregated overall return of an investment, it is difficult for any farm to find the right time to exit from unprofitable use of the technology. Decisions on the termination of unprofitable technology use (after introduction) cannot be made according to rational criteria in the first two years. However, an immediate decision would be necessary, e.g. in M1, which puts farmers in a predicament. They are faced with the dilemma of either exiting too late (on the basis of rational considerations) or exiting too hastily and relying on their intuition. This means the initial decision—before investing— for or against the technology has the greatest impact on operational results.

It has been speculated that the overall low adoption rates of precision agriculture technology by small-scale farms can be explained by the increased complexity of entry and use compared to existing outdated mechanization. Yet this analysis herein shows a more fundamental reason. Farmers using traditional equipment may be reluctant because they recognize the unlikelihood of recovering the costs of digitization. In any case, the scenario of acquisition and non-adoption described in the literature can now be understood from an economic point of view.