Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
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It is critical to analyze the performance of enterprises to achieve sustainable agricultural development. Several studies have been conducted to assess farm performance. However, the studies have been criticized for failing to account for farm heterogeneity (which is frequently unobserved) in their evaluation of Norwegian agricultural performance. Technically, a farm is efficient if it can produce a certain amount of output with the fewest possible inputs and no input waste. In this paper, efficiency scores are calculated using a production function with both a random intercept and a random slope parameter, addressing the issue of unobserved heterogeneity in stochastic frontier analysis. Using Norwegian dairy and crop farms as a case study, we demonstrate the viability of improving the agriculture industry and reducing resource waste. The case study was established on data collected from 5884 dairy farms and 1880 crop farms from the years 2000 to 2019. According to the empirical findings of the case study, dairy and crop producers used inefficient technologies and squandered production resources. If all farmers follow a sustainable and efficient path to produce agricultural output, they could increase output by 15–18%. Farmers must follow sustainable paths, and politicians must encourage farm experience exchange so that less efficient dairy and crop-producing farms can learn from the most efficient farms to achieve sustainable development.
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Eco-efficiency is gaining popularity to measure the agricultural system's economic and environmental performance. The dynamic eco-efficiency of the agricultural system is assessed in this study using a parametric frontier framework that considers the inter-temporal nature of production decisions and methane emissions. We also estimated the static eco-efficiency model for comparison. The empirical analysis is based on 30 years of unbalanced panel data from 692 dairy farms (1991–2020). The generalized method of moment estimation is used to compute dynamic models. Both dynamic and static models show that dairy farms in the study area used available technology inefficiently, which means that some farmers produced lower outputs per input than the best-performing farmers. According to the dynamic eco-efficiency score, dairy farms only generate 94% of the maximum viable output for the input used. If all dairy farms became eco-efficient, an average dairy farm could raise its output by about 6% using the existing technology. According to the projected scores, farmers might improve their eco-efficiency by 10% on average without using more inputs in a static condition. Policymakers should encourage dairy farms to share information with the best-performing dairy farms on how to improve production while considering environmental concerns.
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Habtamu AlemSammendrag
In the economics literature, measuring the performance of a dairy farm with a total productivity index is common practice. Previous research, on the other hand, has been chastised for failing to account for agricultural emissions in their models when calculating resource use productivity. This study estimated green total factor productivity (GTFP) accounting for dairy farms' CH4 emission to the model. The study is based on unbalanced panel data from 692 specialized dairy farms from 1991 to 2020. To estimate GTFP and its components using multiple input–output environmental production technologies, a stochastic input distance function and a Translog model were used. The average annual growth rate of green production over the research period was 0. 032%. The main reason for the increase in GTFP was positive scale change contributions. Technological change (− 0.031% per year) and efficiency change (− 0.002% per year), on the other hand, had a detrimental effect on GTFP.
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Atle Wehn HegnesSammendrag
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This article reports findings from two research projects that aimed to understand the vulnerabilities of cultural heritage sites in Svalbard and investigated factors that influence tourism-induced pressures and site degradation. It draws upon fieldwork conducted at ten selected historic locations, including interviews with tourists and guides, consultations with regional and central cultural heritage management authorities, on-site observations, and condition assessments. The primary goal was to explore indicators rendering cultural heritage sites susceptible to the impacts of tourism and human visitors. These indicators were common denominators and encompassed the sites’ physical state/degree of decay, legibility, accessibility, and quantity and quality of objects at the sites. This article seeks to enhance the understanding of these sites’ vulnerabilities and provide insights for effective heritage site management and sustainable tourism development. The principal findings highlight key factors contributing to cultural heritage sites’ vulnerability. These factors encompass intensity and frequency of visitor traffic, suboptimal visitor management strategies, tourists’ limited awareness of proper site behaviour and conservation practices, and restricted resources for site maintenance and protection. These findings can guide policymakers, site managers, and tourism stakeholders in formulating strategies to balance tourism promotion with site conservation, ensuring the long-term preservation of cultural heritage in this unique and vulnerable environment.