Institution
Indian Institute of Management Ahmedabad
Education•Ahmedabad, India•
About: Indian Institute of Management Ahmedabad is a education organization based out in Ahmedabad, India. It is known for research contribution in the topics: Emerging markets & Population. The organization has 1828 authors who have published 4011 publications receiving 59269 citations. The organization is also known as: IIMA & IIM Ahmedabad.
Papers published on a yearly basis
Papers
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TL;DR: An asymptotic justication for the widely used and em- pirically veried approach of assuming an asymmetric Laplace distribution for the response in Bayesian Quantile Regression by establishing posterior consistency and deriving the rate of convergence under the ALD misspecication.
Abstract: We explore an asymptotic justification for the widely used and empirically verified approach of assuming an asymmetric Laplace distribution (ALD) for the response in Bayesian Quantile Regression. Based on empirical findings, Yu and Moyeed (2001) argued that the use of ALD is satisfactory even if it is not the true underlying distribution. We provide a justification to this claim by establishing posterior consistency and deriving the rate of convergence under the ALD misspecification. Related literature on misspecified models focuses mostly on i.i.d. models which in the regression context amounts to considering i.i.d. random covariates with i.i.d. errors. We study the behavior of the posterior for the misspecified ALD model with independent but non identically distributed response in the presence of non-random covariates. Exploiting the specific form of ALD helps us derive conditions that are more intuitive and easily seen to be satisfied by a wide range of potential true underlying probability distributions for the response. Through simulations, we demonstrate our result and also find that the robustness of the posterior that holds for ALD fails for a Gaussian formulation, thus providing further support for the use of ALD models in quantile regression.
126 citations
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TL;DR: A sustainable low carbon transport (SLCT) scenario based on sustainable strategies for passenger and freight mobility, vehicle technologies and fuel using global CO 2 prices that correspond to 2°C global stabilisation target is presented in this article.
125 citations
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TL;DR: In this article, the authors provide a deep discussion of and look ahead on how technology is changing retail, starting with a classification of technologies that impact retailing, in particular in the COVID-19 and beyond world.
125 citations
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TL;DR: This study explores the feasibility of AI utilization within an organization on six factors such as job-fit, complexity, long-term consequences, affect towards use, social factors and facilitating conditions for different elements of OM by mining the collective intelligence of experts on Twitter and through academic literature.
Abstract: In this digital era, data is new oil and artificial intelligence (AI) is new electricity, which is needed in different elements of operations management (OM) such as manufacturing, product development, services and supply chain. This study explores the feasibility of AI utilization within an organization on six factors such as job-fit, complexity, long-term consequences, affect towards use, social factors and facilitating conditions for different elements of OM by mining the collective intelligence of experts on Twitter and through academic literature. The study provides guidelines for managers for AI applications in different components of OM and concludes by presenting the limitations of the study along with future research directions.
125 citations
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27 Jun 2019TL;DR: This article is distributed under the terms of the Creative Commons AttributionNonCommercial 4.0 License, which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages.
Abstract: 97 Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons AttributionNonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
125 citations
Authors
Showing all 1868 results
Name | H-index | Papers | Citations |
---|---|---|---|
Kanti V. Mardia | 54 | 235 | 20393 |
Mousumi Banerjee | 53 | 193 | 11141 |
Marti G. Subrahmanyam | 52 | 202 | 7641 |
Vishal Gupta | 47 | 387 | 9974 |
Anil K. Gupta | 41 | 175 | 17828 |
Priyadarshi R. Shukla | 39 | 136 | 9749 |
Asha George | 35 | 156 | 4227 |
Ashish Garg | 34 | 246 | 4172 |
Justin Paul | 31 | 119 | 4082 |
Narendra Singh Raghuwanshi | 31 | 136 | 4298 |
Sumeet Gupta | 31 | 108 | 5614 |
Nitin R. Patel | 31 | 55 | 4573 |
Rahul Mukerjee | 30 | 206 | 3507 |
Chandan Sharma | 30 | 124 | 3330 |
Gita Sen | 30 | 57 | 3550 |