Bill DoerrfeldConsultant, Doerrfeld. And for each pitfall, here are few healthier strategies that will help providers bolster their API adoption rates. Even though the advice below will focus on what makes public APIs more appealing, many of the same guidelines can apply to internal API development as well. Testing in the Agile Era:
Researchers use time-series data extensively to explain how the rate of technology adoption varies with time, but time-series data does not address the fundamental reasons for adoption. These three empirical methodologies describe the parts of agricultural technology adoption which must be understood if governments and NGOs are to craft their activities for optimum effect: Technology Adoption Technology is assumed to mean a new, scientifically derived, often complex input supplied to farmers by organizations with deep technical expertise.
This coincidence should not obstruct the point that a technology is simply the application of scientific knowledge for a certain end. A project or a technique can still be considered a technology even if the science is many steps removed from the eventual implementer.
There are many lessons and best practices that can be gleaned from existing studies if technology is looked at in broader terms.
The uncertainty diminishes over time through the acquisition of experience and information, and the production function itself may change as adopters become more efficient in the application of the technology.
In this paper, technology is any discrete input — either as a good or as a method — with the purpose of controlling and managing animal, vegetative growth, or both. This more inclusive concept allows us to look at the adoption dynamics and diffusion patterns of an expanded MERET project using criteria established by a wide body of scholarly research and publications.
The characteristics associated with higher rates of HYV adoption are the same as the ones associated higher participation rates in terrace construction, save for context-specific exemptions.
Just as there are different types of technologies, there are different kinds of adoption. Aggregate adoption, on the other hand, is measured as the aggregate level of use of a particular technology among one specific group of farmers or within one particular area.
In some instances, farmers are presented with a single choice: Similarly with MERET, a community site may be recruited to construct dams, bunds, gully controls and terracing.
This gives farmers several distinct technological options, and it gives those trying to measure and model that adoption more to consider because farmers may adopt the complete package of innovation, they may adopt nothing, or they may pick subsets of bundles.
Doing so produces several simultaneously occurring adoption and diffusion processes, although these processes have been shown to follow specific and predictable patterns. Variable inputs such as HYVs can be adopted in part and planted on a percentage of farmland, and fertilizer can be applied selectively, so modeling their adoption and diffusion involves first measuring if it has been adopted at all, and second assessing the extent to which farmers have adopted it.
Technologies such as wells, tractors and other mechanized inputs are not divisible, thus farmers have only a discrete choice: Modeling this adoption behavior at the individual level produces dichotomous outcomes, but an aggregate analysis turns these discrete choices into continuous measures of the percentage of farmers using the non-divisible inputs.
Ethiopia and MERET Ethiopia is a country so beset by poverty and vulnerability to natural and man-made shocks that it has become synonymous with famine and starvation. It is both one of the poorest countries in Africa17 and one of the most populous. Agencies influenced by this line of thinking have tended to favor direct transfers of food to meet immediate needs.
And when the targeted communities remain food insecure in subsequent years, these aid agencies are left searching for reasons why a one-time in-kind transfer was insufficient for addressing the underlying causes of the original food insecurity.
In the past few decades donors and aid professionals have come to learn that food insecurity is the result of insufficient access to food, not insufficient availability.
The natural resource base is degraded from unsustainable farming practices and forest removal, these unsustainable practices being the byproducts of growing population pressures. These forces locked the growing population out of school, out of the cities, out of non-agricultural work, and consequently forced them to stay on increasingly smaller and more heavily exploited land parcels.
They include soil and stone bunds, gully-control constructions, trenches, bench terracing, water-pond construction, organic fertilizer application, and the planting of strategically chosen tree, shrub and grass varieties.
The program has directly benefited over 1. Indicators showing positive impacts on human wellbeing include: Even with these dual incentives for participation, not all targeted communities choose to take part in MERET, and of those that do opt in, not all of them stay in for the entire five-to-seven years of the project cycle.
Although MERET has been active for over three decades and receives tens of millions of dollars each year, it is still a relatively small project. Governments, aid agencies, and development NGOs can then tailor their agriculture outreach projects to be attractive to their targeted communities.
Factors Influencing Adoption The most often cited factors that have been used to explain the variability seen in agricultural technology adoption and its patterns of diffusion, are those described by Feder, Just and Zilberman. These explanatory indicators vary from study to study based on their contextual applicability, but traditionally include: In delineating these particular factors, they point out that the categories are not discrete or exclusive and that boundaries may blur and overlap due to the interdependent relationship between indicators.
Many studies have shown that each of these indicators significantly influences the agricultural technology adoption process; trying to separate each characteristic from the others is difficult and may even be unnecessary. That is not to suggest uniform causation; farm size may act as a proxy for other socio-economic indicators such as access to credit because the larger farm has more collateral value.
It very well may be the case that these correlated indicators also influence the adoption decision, and therefore a failure to account for them in the regression models may tend to inflate the reported relationship between farm size and adoption likelihoods.
Looking at soil conservation techniques in the Philippines, Shively finds that the decision to adopt depends on farm size, partially because soil conservation on small farms is especially costly due to increases in the short-run risk of consumption shortfall with certainty.Sep 11, · Some estimate the rate of drug errors by doctors has jumped 50 percent in recent years.
Another study found 1 in 5 medications used by seniors are prescribed inappropriately. Cosumerism in Nigeria In: Business and Management Submitted By bumsy Evolution of Consumerism in Nigeria The labor force of Nigeria is roughly million or percent of the population and the unemployment rate is 8%.
Nigeria has experienced strong economic growth averaging percent within the past ten years and inflation . low initial utilization by consumers could be explained by several reasons, including slow adoption of new technology by consumers, lack of perceived ownership and transportability by the consumer, concerns about privacy and security issues, and lack of research .
Reasons For The Slow Adoption Rate Of Consumerism In Nigeria. MASTER DEGREE PROJECT EXCHANGE RATE VARIATION AND INFLATION IN NIGERIA ( ) Master Degree Project in Economics and Finance D-Leval 15 ECTS Spring term Year Onosewalu Okhiria P Taofeek Sesan Saliu P Supervisor: .
8 reasons why your API adoption is so slow Bill Doerrfeld, Consultant, attheheels.com Companies eager to join the API economy often fail in a couple of vital areas. CONSUMERISM IN NIGERIA Dr.
Anthony.A. Ijewere (s enior lecturer) this study identfied those factors that are responsible for the slow growth and activity of consumerism in Nigeria and proffered solution. Key Words: Consumerism, consumer protection, unethical practices, consumer exploitation, In view of the above reasons.