scholarly journals Hold-Up Problems in International Gas Trade: A Case Study

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4984
Author(s):  
Guych Nuryyev ◽  
Tomasz Korol ◽  
Ilia Tetin

The infrastructure required for international natural gas trade is considerable, which often leads to hold-up problems and supply disruptions. This study discusses disruptions of gas supply from Algeria, Indonesia, Russia, and Turkmenistan since the early 1980s. The novelty of this study is its focus on the issues related to transit countries, which are rarely considered in the literature. The results of the study classify supply disruptions into six types, show the evolution of supply disruptions over time, and discuss mitigation strategies. The six types of disruptions include political change, price demands, debts, technical issues, transit fees, theft of gas. The evolution of the disruptions shows that the issues related to transit countries have become more frequent in the last two decades. Mitigation strategies tailored to transit countries include using an international organisation, designing contracts with price mechanisms that might reduce the possibility of disputes and reducing the number of parties involved in the trade.

2010 ◽  
Vol 19 (3) ◽  
pp. 299 ◽  
Author(s):  
J. L. Beverly ◽  
P. Bothwell ◽  
J. C. R. Conner ◽  
E. P. K. Herd

We assessed the exposure of the built environment to potential ignition sources generated from vegetative fuel for four communities in the province of Alberta, Canada. Ignition processes generated by burning vegetation that were included in the analysis were radiant heat, short-range spotting, and longer-range spotting. Results were used to map the boundaries of the wildland–urban interface and to delineate zones within each community that identify the degree to which these areas represent potential wildfire entry-points into the wildland–urban interface. The assessment method can be used to set priorities for mitigation activities; compare conditions within and between communities and over time; and identify priority areas for time- and resource-intensive site assessments that are often completed for individual structures located in the wildland–urban interface. We compared results among the four case-study communities and demonstrated an application of the approach for evaluating community fuel treatment plans. Factors that influenced the exposure of the built environment to potential ignition sources differed among the communities, which suggested the need for community-specific mitigation strategies. Spatial patterns of areas with elevated ignition exposure reflected not only the amount of ignition-producing vegetation around the built environment, but also the size and arrangement of fuel patches in relation to the unique morphology of the community and the occurrence of occluded interface zones.


2020 ◽  
Vol 254 ◽  
pp. 120066 ◽  
Author(s):  
Shaghayegh Khayat Basiri ◽  
Farzad Movahedi Sobhani ◽  
Seyed Jafar Sadjadi
Keyword(s):  

2019 ◽  
Vol 222 ◽  
pp. 414-423 ◽  
Author(s):  
Eleni Strantzali ◽  
Konstantinos Aravossis ◽  
Georgios A. Livanos ◽  
Christos Nikoloudis

Energy Policy ◽  
2009 ◽  
Vol 37 (3) ◽  
pp. 799-812 ◽  
Author(s):  
Maryam Hamedi ◽  
Reza Zanjirani Farahani ◽  
Mohammad Moattar Husseini ◽  
Gholam Reza Esmaeilian

2021 ◽  
Vol 5 (GROUP) ◽  
pp. 1-24
Author(s):  
Jumana Almahmoud ◽  
Robert DeLine ◽  
Steven M. Drucker

Machine learning (ML) has become a crucial component in software products, either as part of the user experience or used internally by software teams. Prior studies have explored how ML is affecting development team roles beyond data scientists, including user experience designers, program managers, developers and operations engineers. However, there has been little investigation of how team members in different roles on the team communicate about ML, in particular about the quality of models. We use the general term quality to look beyond technical issues of model evaluation, such as accuracy and overfitting, to any issue affecting whether a model is suitable for use, including ethical, engineering, operations, and legal considerations. What challenges do teams face in discussing the quality of ML models? What work practices mitigate those challenges? To address these questions, we conducted a mixed-methods study at a large software company, first interviewing15 employees in a variety of roles, then surveying 168 employees to broaden our understanding. We found several challenges, including a mismatch between user-focused and model-focused notions of performance, misunderstandings about the capabilities and limitations of evolving ML technology, and difficulties in understanding concerns beyond one's own role. We found several mitigation strategies, including the use of demos during discussions to keep the team customer-focused.


Energy Policy ◽  
2009 ◽  
Vol 37 (9) ◽  
pp. 3708
Author(s):  
Maryam Hamedi ◽  
Reza Zanjirani Farahani ◽  
Mohammad Moattar Husseini ◽  
Gholam Reza Esmaeilian

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