ECONOMIC FACTORS INFLUENCING THE LEVEL OF ECONOMIC DEVELOPMENT OF MULTICOUNTY AREAS

Community/Rural/Urban Development,

INFORMATION AND THE ADOPTION OF PRECISION FARMING TECHNOLOGIES

Precision farming technologies have been commercially available since the early 1990s, but the pace of adoption among U.S. farmers has been modest. This study examines the relationship between the adoption of diagnostic and application techniques of precision farming and sources of information available to farmers about precision farming. The model used in the analysis accounts for sources of self-selection in the adoption process that could bias the results. Results indicate interpersonal information sources have increased adoption relative to information from the mass media, and the private sector has been the driving force behind the diffusion of precision farming. Information from crop consultants and input suppliers has had the greatest impact on the adoption of precision farming technologies. These sources likely provide the greatest technical expertise about precision farming, and thus are better equipped to ease the significant human capital requirement of precision farming technologies.information sources, logit analysis, precision farming, self-selection bias, technology adoption, Farm Management, Research and Development/Tech Change/Emerging Technologies,

INFORMATION AND THE ADOPTION OF PRECISION FARMING

This study examines the relationship between precision farming information sources and precision farming adoption. The analysis accounts for the fact that not all farmers are aware of precision farming techniques and that those who are aware may not be a random sample. Results indicate that many information sources increase adoption relative to information only from the media, but contact with crop consultants has had the greatest impact on the adoption of precision farming technologies.Farm Management,

FACTORS AFFECTING THE LIKELIHOOD OF CORN ROOTWORM BT SEED ADOPTION

The likelihood of adopting corn rootworm (CRW) Bt seed technology was analyzed using an ordered logit model. Data used to estimate the model came from USDAs 2001 Agricultural Resource Management Survey. Statistically significant variables include operator age, farm type, farm size, rootworm loss and current treatment for rootworm, off farm labor, and Bt technology for corn borer. The likelihood of adoption was not related to crop rotation, tillage system, new variant CRW region, or education.Crop Production/Industries,

DECOMPOSING THE SIZE EFFECT ON THE ADOPTION OF INNOVATIONS: AGROBIOTECHNOLOGY AND PRECISION FARMING

This study contrasts the relationship between farm-size and adoption for two types of innovations, genetically engineered crops and precision farming, controlling for other factors. The analysis uses an extension of the McDonald and Moffit decomposition for the two-limit Tobit model.Research and Development/Tech Change/Emerging Technologies,

Work 4.0 and the Need for Boundary-Spanning

The evolution of a digital world driven by and generating substantial volumes of data is also changing the way people work and associated specializations, characterized as ‘Work 4.0’ in Europe. Smart devices and the use of data analytics is getting work done more effectively but new skills are needed to develop and use these tools. Agility is a requisite capability. Different communities of practice need to work together, possibly with new kinds of users, introducing a need for enhanced boundary-spanning skills and tools. Boundary-spanning activities take place at multiple organizational levels. Teams use boundary object tools as alignment mechanisms, but also create boundary objects (e.g. prototypes) to test alignment. Case observations from agile IS projects associated with large and small firms highlight the influence of context, a need for the use of multiple complementary boundary objects and for learning to use them effectively

U.S. Corn Producer’s Response to Increased Energy Prices: Evidence from Producer Surveys in 2001 and 2005

Crop Production/Industries, Risk and Uncertainty,

Work 4.0 and the Identification of Complex Competence Sets

In our progressively more interconnected world, some people may be displaced from their traditional occupations by intelligent agents and smart machines. At the same time there may be a shortage of people skilled in the development of these technologies, and societal changes may see more people undertaking a succession of short-term project assignments. This is leading to studies of future competency requirements (called Work 4.0 in Europe) and the evolution of agile human resources management systems. A focus on mapping accessible individual competence sets is emerging, facilitated by the identification of associated information systems. In this paper we explore challenges in the identification of current and future competency requirements and in competency mapping to facilitate agile operations. We also introduce the concept of competency relationship mapping

Working-Land Conservation Structures: Evidence on Program and Non-Program Participants

In recent years, the Federal government has placed more emphasis on working-land conservation programs. Farmers can be reimbursed for adopting certain conservation practices, such as the installation of in-field or perimeter conservation structures, to enhance water quality and soil productivity. In an effort to better understand the relationships between operator motivations, program incentives, and the environmental benefits of conservation programs, a multi-agency survey, the Conservation Effects Assessment Project-Agricultural Resources Management Survey (CEAP-ARMS), was conducted in 2004 across 16 states representing more than one-million farmers growing wheat. The nationally representative survey integrates Natural Resources Inventory (NRI) data on field-level physical characteristics, program information, farm-level costs of production, and farm household information. This objective of this paper is twofold. First, using the CEAP-ARMS, farm structure, household, and operator characteristics of farmers participating in one or more conservation programs are compared with farmers not participating in a conservation program. Second, an impact model is specified to test whether program participants allocated more acres to in-field or perimeter conservation structures than nonparticipants, holding other factors constant. Evidence suggests that program participants allocate more field acres to vegetative conservation structures than nonparticipants with in-field or perimeter conservation structures.Environmental Economics and Policy,