Enterprise innovation has gained the interest of development policymakers and scholars as the bases for the industrial development. This study comprehensively analyzes the drivers of enterprise innovation in developing countries. The study uses survey data to analyze the determinants of enterprise innovation in Ethiopia using a multivariate probit (MVP) model. For this study, enterprises were grouped into four categories: all-sized, large-sized, medium-sized, and micro-and small-sized enterprises. It appears that engagement in R & D, on-the-job training, and website ownership significantly determine enterprise innovation. This study, unlike previous studies, comprehensively analyzes drivers of innovation by considering enterprises in different sizes and all at the same time. This helps identify factors most relevant for enterprise innovation at all stage which help policymakers get focused on strategy development. Based on the findings, further emphasis on engagement in R & D would help enterprises to become innovative for all categories of enterprises. Furthermore, strengthening the available formal training and diversifying type of the training that is related to skills, knowledge, and techniques that help achieve the long-term objective of the enterprises are worth considering. Enterprises also need to subscribe to different sites that help learn more and access information.
Energy plays critical role in bringing the sustainable development. However, when not used efficiently, its negative consequences on any economy is enormous. This could be related to threatening the sustainable development of the economy, energy security and worsening the environmental conditions (Adom and Kwakwa 2014). Challenges like climate change and energy security that world economy is facing the in the twenty first century is mainly due to energy consumption. Since anthropogenic emissions of carbon dioxide (CO 2) result predominantly from the combustion of fossil fuels, energy consumption is at the focus of the climate change debate. According to U.S Energy Information and Administration (EIA) (2016), world energy-related CO 2 emissions increase from 32.3 billion metric tons in 2012 to 35.6 billion metric tons in 2020 and to 43.2 billion metric tons in 2040. Efficient energy utilization has a great role in an economy. Promoting energy efficiency has several potential benefits which consist of promoting market
This study analyzes the technical efficiency and production risk of 862 maize farmers in major maize producing regions of Ethiopia. It employs the stochastic frontier approach (SFA) to estimate the level of technical efficiencies of stallholder farmers. The stochastic frontier approach (SFA) uses flexible risk properties to account for production risk. Thus, maize production variability is assessed from two perspectives, the production risk and the technical efficiency. The study also attempts to determine the socio-economic and farm characteristics that influence technical efficiency of maize production in the study area. The findings of the study showed the existence of both production risk and technical inefficiency in maize production process. Input variables (amounts per hectare) such as fertilizer and labor positively influence maize output. The findings also show that farms in the study area exhibit decreasing returns to scale. Fertilizer and ox plough days reduce output risk while labor and improved seed increase output risk. The mean technical efficiency for maize farms is 48 percent. This study concludes that production risk and technical inefficiency prevents the maize farmers from realizing their frontier output. The best factors that improve the efficiency of the maize farmers in the study area include: frequency of extension contact, access to credit and use of intercropping. It was also realized that altitude and terracing in maize farms had influence on farmer efficiency.
Deforestation and poverty are challenging problems in Ethiopia. The deforestationpoverty nexus is complicated by the institutional failures related to management of natural resources. This study was conducted to analyse the determinants of deforestation in Ethiopia, Western Oromia the case of Komto forest in East Wollega Zone employing primary cross-sectional data on the sampled households. Multistage sampling technique was used in selecting 150 household head respondents. Volume of woody biomass consumed and sold in meter cube was used to measure deforestation. The result of the Heckman maximum likelihood model estimates showed that large landholding size reduces deforestation significantly. It was also found that forest product sale, and corruption behaviour of households and staff of institution aggravates deforestation. Probability of forest product use is negatively related to kerosene use and positively to road access, purpose of use, and corruption perception significantly. The study showed that poverty and institutional failure related to the forest management are key factors determining deforestation /forest degradation in the study area. Thus solving poverty and institutional failures would help solve deforestation problem of the study area.
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