Globally, agriculture is on a cross road with pressing challenges of ever increasing demand in the face of declining availability (and deterioration in functional quality) of key natural resources (mainly water, cultivable land, soil), climate change and volatility in market and regulatory conditions. To survive amid these challenges, technologies hoped to improve productivity and overall performance of agriculture have been promoted. However, utilization does not leave up to expectations. This study identifies three gaps: (a)methodological limitations in modelling technology adoption behavior particularly in the presence of interdependence in users’ adoption decision across related technologies; (b) failure to incorporate farmers’ knowledge, perception, views, concerns and needs resulting in lack of adapted solutions based on real needs; and (c) lack of evidence on expected costs and benefits of technologies under local conditions. The study seeks to fill part of the gap in these issues with the objective of contributing to the advancement of understanding and facilitation of efforts to beneficial adoption oftechnological solutions in agriculture. To address its objectives, the study us ed data from several sources and employed a combination of relevant methods. The thesis consists of four selfcontained but related papers two of which focus on ex-post statistical mod lling of adoption behavior using observational data. The focus on the first paper is the use of context relevantmodels to adequately model farm households’ interdependent adoption decisions considering five innovations/inputs (row planting, fertilizer, improved seed, extension and advisory service) using panel data from Ethiopia. The second paper intends to identify important operator and farm-related factors that influence adoption of auto-guidance and GPS-assisted precision agriculture (PA) using cross section survey data from Denmark and Germany. The third paper explore farmers’ views and needs in relation to a young technology called Controlled Traffic Farming (CTF). The fourth paper is concerned with evaluating economic advantage of an integrated precision farming technology for irrigation and harvest management (labelled as USERPA technology). The technologies considered in papers II–IV are in the domain of PA. Main findings from the thesis: (i) farmers do consider multiple technologies in their adoption decisions, i.e., there exist strong interdependence in farm households’ adoption decision of related technologies. (ii) Scale of operation (farm size) does have a significant bearing on the adoption of PA technologies. (iii) Among surveyed European farmers, there is positive perception and optimistic expectation about the potential of CTF but adoption is hindered by technical (e.g., compatibility) and economic (e.g., cost of machinery modification, RTK, specialized equipment) and access (availability of needed equipment in locality) related factors. (iv) Economic value of USERPA (relative to conventional practice in the case study area) is highly sensitive to changes in fruit price and cost of sensors. The findings of the study suggest for: (a) comprehensive modelling of interdependent decisions, (b) adapted market models (e.g, adapted contractual service provision in collaboration with farming associations) to minimize fixed cost associated with the technologies in consideration and enable optimal use of resources and (c) regulatory interventions to facilitate standardization and compatibility of technologies from different suppliers. The main lesson during the course of the study and the message from the papers combined is ‘ meaningful understanding and beneficial facilitation of technology adoption demands putting pieces together with coordination of efforts’.