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dc.contributor.advisorNarahari, Y
dc.contributor.authorUdaya Lakshmi, L
dc.date.accessioned2014-06-05T07:34:41Z
dc.date.accessioned2018-07-31T04:38:27Z
dc.date.available2014-06-05T07:34:41Z
dc.date.available2018-07-31T04:38:27Z
dc.date.issued2014-06-05
dc.date.submitted2012
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/2322
dc.identifier.abstracthttp://etd.iisc.ac.in/static/etd/abstracts/2986/G25276-Abs.pdfen_US
dc.description.abstractGlobal warming is currently a major challenge faced by the world. Reduction of carbon emissions is of paramount importance in the context of global warming. There are widespread ongoing efforts to find satisfactory ways of surmounting this challenge. The basic objective of all such efforts can be summarized as conception and formation of protocols to reduce the pace of global carbon levels. Countries and global companies are now engaged in understanding systematic ways of achieving well defined emission targets. In this dissertation, we explore the specific problem faced by a global industry or global company in allocating carbon emission reduction units to its different divisions and supply chain partners in achieving a required target of reductions in its carbon reduction program. The problem becomes a challenging one since the divisions and supply chain partners are often autonomous and could exhibit strategic behavior. Game theory and mechanism design provide a natural modeling tool for capturing the strategic dynamics involved in this problem. DSIC (Dominant Strategy Incentive Compatibility), AE (Allocative Efficiency), and SBB (Strict Budget Balance) are the key desirable properties for carbon reduction allocation mechanisms. But due to an impossibility result in mechanism design, DSIC, AE, and SBB can never be simultaneously achieved. Hence in this dissertation, we offer as contributions, two elegant solutions to this carbon emission reduction allocation problem. The first contribution is a mechanism which is DSIC and AE. We first propose a straightforward Vickrey-Clarke-Groves (VCG) mechanism based solution to the problem, leading to a DSIC and AE reverse auction protocol for allocating carbon reductions among the divisions. This solution, however, leads to a high level of budget imbalance. To reduce budget imbalance, we use redistribution mechanisms, without affecting the key properties of DSIC and AE. The Cavallo-Bailey redistribution mechanism, when applied to the above reverse auction protocol leads to reduced budget imbalance. To reduce the imbalance further, we propose an innovative forward auction protocol which achieves less imbalance when combined with the Cavallo-Bailey redistribution mechanism. The forward auction protocol also has the appealing feature of handsomely rewarding divisions that reduce emissions and levying appropriate penalties on divisions that do not participate in emission reductions. The second contribution is a DSIC and SBB mechanism. Even though the first mechanism tries to reduce the budget imbalance, there is always a surplus which cannot be distributed among divisions and is wasted. So, in this part, by slightly compromising on efficiency, we propose a mechanism which is DSIC and SBB. The SBB property guarantees that there is no need for any monetary support from an external agency for implementing the mechanism and there is no leakage of revenue.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesG25276en_US
dc.subjectGame Theoryen_US
dc.subjectAllocationsen_US
dc.subjectAir Pollutionen_US
dc.subjectCarbon Emissionen_US
dc.subjectCarbon Footprinten_US
dc.subjectCarbon Emission Reduction Allocationen_US
dc.subjectMechanism Designen_US
dc.subjectDominant Strategy Incentive Compatibility (DSIC)en_US
dc.subjectAllocative Efficiency (AE)en_US
dc.subjectStrict Budget Balance (SBB)en_US
dc.subject.classificationEnvironmental Engineeringen_US
dc.titleDesign Of Truthful Allocation Mechanisms For Carbon Footprint Reductionen_US
dc.typeThesisen_US
dc.degree.nameMSc Enggen_US
dc.degree.levelMastersen_US
dc.degree.disciplineFaculty of Engineeringen_US


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