Auflistung nach Autor:in "Bonke, Vanessa"
1 - 2 von 2
Treffer pro Seite
Sortieroptionen
- KonferenzbeitragInvestigating the adoption of smartphone apps in crop protection(40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier, 2020) Michels, Marius; Bonke, Vanessa; Mußhoff, OliverBased on an online survey of 207 German farmers conducted in 2019, we investigated farmers’ adoption decision for crop protection smartphone apps based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework applying partial least squares equation modelling and a binary logit model. Descriptive results show that 95 % of the surveyed farmers use a smartphone, but only 71 % use a crop protection smartphone app. Apps providing information about weather, pest scouting and infestations forecasts are perceived as most useful by the majority of farmers. However, reported use fell short of reported usefulness. All hypotheses of the UTAUT model could be verified. 73 % of the variation in the behavioral intention to use a crop protection smartphone app and 50 % of the variation in the actual adoption is explained by the model.
- KonferenzbeitragTiming of Smartphone Adoption in German Agriculture – Who are the Early Adopters?(41. GIL-Jahrestagung, Informations- und Kommunikationstechnologie in kritischen Zeiten, 2021) Michels, Marius; Bonke, Vanessa; Mußhoff, OliverSmartphones suit several on-farm operational activities and farmers’ daily working routine very well due to their mobility, high computing power and ability to install (agricultural) apps as needed. However, no study has yet focused on factors affecting the timing of adoption. Understanding the timing of a technology adoption and identifying characteristics of early and late adopters is consequently of great relevance to further anticipate the innovation diffusion process. The aim of this study is therefore to analyze the timing of smartphone adoption by applying a tobit regression model to a data set of 207 German farmers collected in 2019. Regression results show that, among other factors, farmers’ age and risk attitude affect the timing of smartphone adoption.