Economics and Price Risks in International Pellet Supply Chains

Ehrig, Rita; Behrendt, Frank; Wörgetter, Manfred; Strasser, Christoph

doi:10.1007/978-3-319-07016-2

Cited by 8 publications

(13 citation statements)

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“…Review of the theoretical relationship with the price according to risk (Ehrig et al, 2014;Williams, 2014) can be seen in Figure 3. Risk has a high effect on the price; the higher the risk, the greater the impact on prices (Ramirez, 2000;Travisi & Nijkamp, 2008).…”

Section: Conceptual Model Factors That Influence the Riskbased Formulmentioning

confidence: 99%

“…Some studies related to the preparation of the prices were reported by Septiani et al (2014), Kumawat et al (2014), Isermeyer et al (2003), Hemme et al (2014), Sobczyński et al (2013), and Ehrig et al (2014). Based on the description of the above issues, the formulated goal of the research is a risk-based modeling calculations of the price of milk at the dairy farmer level, consisting of three sub-goals, namely: (1) determining the adjustment factor of risk in the variable cost of production of dairy cattle farming, (2) developing detailed production costs of dairy cattle farming by including the adjustment factor of risk, (3) calculating the basic price of milk per liter based on the total cost of production with the risk model been relied upon to be an early model for the parties concerned in determining the price of milk at the farmer level with considerable risk.…”

Section: Introductionmentioning

confidence: 99%

“…The production costs consist of fixed costs and variable costs (Horngren et al, 2012). These costs are heavily influenced by the risks involved in the activities undertaken by farmers (Sobczyński et al, 2013;Ehrig et al, 2014;Williams, 2014). The elasticity of supply price and the price of fresh milk concentrates on individual farmer level is sufficiently high, where dairy production is highly responsive to these two variables.…”

Section: Introductionmentioning

confidence: 99%

“…The decision depends on many other factors beyond the capability of the farmers to control (Colicchia & Strozzi, 2012;Ehrig et al, 2014;Williams, 2014). According to Bunn (1999), Tsolakis et al (2014), Marra et al (2012), the high variability in production have led to an increase in price variability.…”

Section: Introductionmentioning

confidence: 99%

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Risk Based Milk Pricing Model at Dairy Farmers Level

Septiani

Marimin

Herdiyeni

et al. 2017

Med Pet

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The milk price from a cooperative institution to farmer does not fully cover the production cost. Though, dairy farmers encounter various risks and uncertainties in conducting their business. The highest risk in milk supply lies in the activities at the farm. This study was designed to formulate a model for calculating milk price at farmer's level based on risk. Risks that occur on farms include the risk of cow breeding, sanitation, health care, cattle feed management, milking and milk sales. This research used the location of the farm in West Java region. There were five main stages in the preparation of this model, (1) identification and analysis of influential factors, (2) development of a conceptual model, (3) structural analysis and the amount of production costs, (4) model calculation of production cost with risk factors, and (5) risk based milk pricing model. This research built a relationship between risks on smallholder dairy farms with the production costs to be incurred by the farmers. It was also obtained the formulation of risk adjustment factor calculation for the variable costs of production in dairy cattle farm. The difference in production costs with risk and the total production cost without risk was about 8% to 10%. It could be concluded that the basic price of milk proposed based on the research was around IDR 4,250-IDR 4,350/L for 3 to 4 cows ownership. Increasing farmer income was expected to be obtained by entering the value of this risk in the calculation of production costs.Keywords: production cost, milk price, risk, dairy farmer, income ABSTRAK Harga susu yang diterima peternak dari koperasi saat ini belum sepenuhnya dapat menutupi biaya produksi. Padahal peternak di dalam menjalankan usahanya menghadapi berbagai risiko dan ketidakpastian. Risiko terbesar dalam rantai pasok susu terletak pada kegiatan di peternakan. Penelitian ini bertujuan untuk merumuskan model perhitungan harga susu di tingkat peternak berbasis risiko. Risiko yang terjadi di peternakan di antaranya risiko pembibitan sapi, sanitasi, pemeliharaan kesehatan sapi, manajemen pakan, pemerahan, dan penjualan susu. Lima tahapan utama dalam penyusunan model ini ialah (1) identifikasi dan analisis faktor yang berpengaruh, (2) membangun model konseptual, (3) analisis struktural dan besaran biaya produksi, (4) model perhitungan biaya produksi dengan faktor risiko, dan (5) model harga susu berbasis risiko. Penelitian ini membangun hubungan antara risiko di peternakan dengan biaya produksi yang harus dikeluarkan oleh peternak, seperti biaya penyusutan kandang dipengaruhi oleh risiko kontruksi kandang yang tidak memenuhi syarat dan biaya lainnya. Selain itu juga diperoleh formulasi perhitungan faktor penyesuaian risiko untuk variabel biaya produksi usaha sapi perah. Perbedaan biaya produksi dengan risiko dan biaya produksi total tanpa risiko sekitar 8% sampai dengan 10%. Dapat disimpulkan bahwa harga dasar susu yang diusulkan berdasarkan hasil penelitian ini pada kepemilikan ternak 3-4 ekor sapi berkisar Rp 4,250-Rp 4,350/...

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Section: Conceptual Model Factors That Influence the Riskbased Formulmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Risk Based Milk Pricing Model at Dairy Farmers Level

Septiani

Marimin

Herdiyeni

et al. 2017

Med Pet

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show abstract

“…Cultivation and transport emissions of feedstock consumed for drying purposes were allocated to pelletizing emissions. Energy consumption for the different pelletizing components was taken from several literature studies, with the average of multiple values being used [38][39][40][41][42][43][44]. During pelletization, a loss of 1% feedstock was assumed.…”

Section: Processingmentioning

confidence: 99%

The Potential Contribution of Imported Biomass to Renewable Energy Targets in the EU–the Trade-off between Ambitious Greenhouse Gas Emission Reduction Targets and Cost Thresholds

2020

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Wood pellets could potentially contribute to bioenergy demand in the European Union (EU). Market cost constraints as well as greenhouse gas (GHG) emission savings thresholds imposed by the European Commission however limit the potential use of pellets. A spatially explicit assessment of import potentials of both pellets and torrefied pellets, based on the growing stock of forestry biomass in the US, Canada, Brazil, Russia and Baltic States, was combined with an analysis of supply chain costs and emissions in order to analyse potentials as limited by different levels of costs and emission constraints. Results show that in case of GHG savings thresholds of 70%, 80% and 85% the total import potential is reduced to 61 to 24 and 1 Mt, respectively. The potential for torrefied pellets is larger in all cases, 44 Mt in the case of an 80% limit. Import potentials at cost limits of 200, 175, 150 and 125 €/t are reduced from 58 Mt to 52, 38 and 9 Mt pellets, respectively, with little difference between pellets and torrefied pellets. This work shows that spatially explicit variation in feedstock availability and logistics has a significant impact on total import potentials and must therefore be included in any assessment of bioenergy potential and trade.

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Sourcing overseas biomass for EU ambitions: assessing net sustainable export potential from various sourcing countries

Mai-Moulin

Fingerman

Elbersen

et al. 2018

Biofuels Bioprod Bioref

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Low‐cost sustainable biomass availability in the European Union may not be able to meet increasing demand; exploring the option of importing biomass is therefore imperative for the years to come. This article assesses sustainable biomass export potential from Brazil, Colombia, Indonesia, Kenya, Ukraine, and the United States by applying a number of sustainability criteria. Only biomass types with the highest potential are selected, to take advantage of economies of scale, e.g. pulpwood, wood waste, and residues in the United States, and agricultural residues in Ukraine. This study found that, except for the United States, pellet markets in the sourcing regions are largely undeveloped. The export potential depends strongly on pellet mill capacity and assumed growth rates in the pellet industry. Results show that the United States, Ukraine, Indonesia, and Brazil offer the highest biomass export potential. In the Business As Usual 2030 scenario, up to 204 PJ could potentially be mobilized; in the High Export scenario this could increase to 1423 PJ, with 89% of the potential being available for costs ranging from 6.4 to 15 €/GJ. These potentials meet the European Commission requirements for a 70% reduction in greenhouse gas emissions set in the Renewable Energy Directive. The total export potentials do not reflect the net possible import potentials to the European Union, as biomass could be imported to other countries where there is a demand for it, where less strict sustainability requirements are applied, and which are proximate to the sourcing regions, notably South Korea, Japan, and China. © 2018 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

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Economics and Price Risks in International Pellet Supply Chains

Cited by 8 publications

References 0 publications

Risk Based Milk Pricing Model at Dairy Farmers Level

Risk Based Milk Pricing Model at Dairy Farmers Level

The Potential Contribution of Imported Biomass to Renewable Energy Targets in the EU–the Trade-off between Ambitious Greenhouse Gas Emission Reduction Targets and Cost Thresholds

Sourcing overseas biomass for EU ambitions: assessing net sustainable export potential from various sourcing countries

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