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Delaying investments in sensor technology: The rationality of dairy farmers' investment decisions illustrated within the framework of real options theory.
Rutten, C J; Steeneveld, W; Oude Lansink, A G J M; Hogeveen, H.
Afiliación
  • Rutten CJ; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, the Netherlands.
  • Steeneveld W; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, the Netherlands. Electronic address: w.steeneveld@uu.nl.
  • Oude Lansink AGJM; Chair group Business Economics, Wageningen University, Hollandseweg 1, 6706 KN Wageningen, the Netherlands.
  • Hogeveen H; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, the Netherlands; Chair group Business Economics, Wageningen University, Hollandseweg 1, 6706 KN Wageningen, the Netherlands.
J Dairy Sci ; 101(8): 7650-7660, 2018 Aug.
Article en En | MEDLINE | ID: mdl-29729913
ABSTRACT
The adoption rate of sensors on dairy farms varies widely. Whereas some sensors are hardly adopted, others are adopted by many farmers. A potential rational explanation for the difference in adoption may be the expected future technological progress in the sensor technology and expected future improved decision support possibilities. For some sensors not much progress can be expected because the technology has already made enormous progress in recent years, whereas for sensors that have only recently been introduced on the market, much progress can be expected. The adoption of sensors may thus be partly explained by uncertainty about the investment decision, in which uncertainty lays in the future performance of the sensors and uncertainty about whether improved informed decision support will become available. The overall aim was to offer a plausible example of why a sensor may not be adopted now. To explain this, the role of uncertainty about technological progress in the investment decision was illustrated for highly adopted sensors (automated estrus detection) and hardly adopted sensors (automated body condition score). This theoretical illustration uses the real options theory, which accounts for the role of uncertainty in the timing of investment decisions. A discrete event model, simulating a farm of 100 dairy cows, was developed to estimate the net present value (NPV) of investing now and investing in 5 yr in both sensor systems. The results show that investing now in automated estrus detection resulted in a higher NPV than investing 5 yr from now, whereas for the automated body condition score postponing the investment resulted in a higher NPV compared with investing now. These results are in line with the observation that farmers postpone investments in sensors. Also, the current high adoption of automated estrus detection sensors can be explained because the NPV of investing now is higher than the NPV of investing in 5 yr. The results confirm that uncertainty about future sensor performance and uncertainty about whether improved decision support will become available play a role in investment decisions.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Industria Lechera / Detección del Estro / Inversiones en Salud Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Industria Lechera / Detección del Estro / Inversiones en Salud Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2018 Tipo del documento: Article