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Purpose The purpose of this paper is to empirically investigate the influencing factors of loan demand in agriculture. With the structural changes that agriculture is undergoing and the accordingly higher financing requirements and volumes, the analysis of loan demand in agriculture is of particular interest. Design/methodology/approach Detailed actual loan data at farm level, which is provided by a major German development bank for the agricultural sector, is used for the analysis. The data set covers the period from 2010 to 2014 and consists of 68,430 observations. Due to the data structure, an ordinary least square regression is conducted with the loan amount as the dependent variable. Many explanatory variables are included, such as the interest rate, the intended use of the loan, grace periods, the gross value added (GVA) and the business climate index for agriculture. Findings Amongst others, the authors find that interest rate, GVA, grace periods and farmers’ business expectations have significant effects on the loan demand in agriculture. According to the results, the interest rate has a significant negative effect, whereas the granted grace periods, the GVA in agriculture and farmers’ business expectations have significant positive effects on the loan demand. Originality/value This paper investigates the determinants of loan demand in agriculture in a developed country by using unique and comprehensive data at loan and farm level. Amongst others, elasticities of loan demand in agriculture are determined.

By providing additional information and simulating results, decision support tools are one of the methods to enhance a farmer's decision-making process in order to achieve more sustainable practices. With the latest developments in smartphone technology, new possibilities to integrate decision support tools into the daily work process have been emerging and smartphone apps related to crop protection have been developed. However, little is known about the utilization of smartphones by farmers in general, and specifically with regard to crop protection. In order to gather first insights into the factors that could affect the decision of farmers to integrate smartphones and crop protection-related apps in particular, into their work process, we conducted an online survey with 174 technologically experienced German farmers in 2017. We gained insights about the current use of smartphones from the surveyed German farmers, explored which topics farmers perceive as useful in the form of an app for crop protection, and which factors influence the willingness to pay for these apps. Our results show that 93% of the respondents use smartphones for agricultural purposes. Weather forecasts, tools to identify pests, diseases and weeds, as well as related forecasts are perceived as useful by the majority of respondents. Eighty-two percent of the respondents are generally willing to pay for crop protection apps. Using a probit model, we found that the farmer's age, farm size, knowledge about specific crop protection apps, potential for cost reduction, and potential to reduce negative environmental effects have an influence on the general willingness to pay. Overall, this is the first study to explore factors influencing the willingness to pay for crop protection apps and assess which types of apps are perceived as useful by technologically experienced German farmers.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu Terms of use: Documents in AbstractThe internet is playing an increasing role in the development of rural areas. For farmers in particular, reliable internet access creates opportunities concerning farm management decisions. Hence, the goal of this study was to investigate German farmers' willingness to buy inputs online. Primary data was collected by conducting a discrete choice experiment about the purchase of crop protection products. Selection decisions of 165 arable farmers were analyzed by a generalized multinomial logit model (GMNL) resulting in willingness to accept (WTA) space estimation. WTA estimates show that farmers are willing to switch to an online merchant if they are offered a significantly lower price. However, word-of-mouth-reputation and consultation offered via traditional media do not influence farmers' WTA for an online merchant. In contrast, delivery time significantly affects farmers' WTA for inputs purchased online. We also show that farmers' risk attitudes, prior online shopping experiences, and education are influential factors for the WTA for an online merchant. Surprisingly, age and farm size do not impact farmers' WTA. Since e-commerce has not been widely established in agriculture yet, these results are of great practical importance. The findings of this study give online merchants of agricultural inputs a first orientation for choosing appropriate marketing measures. Moreover, results are interesting for education policy.

Mobile internet is considered one of the most important developments in information and communication technology due to its considerable effect on both the economy and our daily lives. Furthermore, mobile internet is an essential tool for overcoming the rural–urban digital divide. With respect to agriculture, mobile internet can play a central role in information gathering as well as the implementation of precision and smart farming technologies. Yet, no study has identified the determinants of mobile internet adoption in agriculture. Using a bivariate probit model with a sample selection and a representative data set from 815 German farmers, this study showed that, among other characteristics, the age of the farmer, farm size and location, as well as familiarity with internet risks is associated with mobile internet adoption in agriculture. These results may be of interest to policy makers, who deal with internet infrastructure, and providers of farm equipment that rely on mobile internet connection. [EconLit citations: Q16].