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: Context (language use) & Emerging markets. 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
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TL;DR: In this article, the authors examine an apparel serial supply chain whose players initiate product "greening" and study the impact of greening costs and consumer sensitivity towards green apparels.
474 citations
The Chinese University of Hong Kong1, City University of Hong Kong2, University of Macau3, Simón Bolívar University4, University of Tokyo5, University of Osnabrück6, California State University, Chico7, University of Vienna8, Katholieke Universiteit Leuven9, University of Alberta10, University of Guelph11, Chinese Academy of Sciences12, Academy of Sciences of the Czech Republic13, Charles University in Prague14, Pedagogical University15, Åbo Akademi University16, University of Lyon17, Tbilisi State University18, International University, Cambodia19, Hong Kong Polytechnic University20, Hungarian Academy of Sciences21, National and Kapodistrian University of Athens22, University of Delhi23, Indian Statistical Institute24, Indian Institute of Management Ahmedabad25, Padjadjaran University26, University of Haifa27, University of Padua28, Seowon University29, University of Latvia30, American University of Beirut31, Universiti Sains Malaysia32, Universiti Malaysia Sabah33, Tilburg University34, Victoria University of Wellington35, University of Lagos36, University of Bergen37, University of Peshawar38, University of the Philippines39, University of Porto40, University of Minho41, Russian Academy of Sciences42, University of Cape Town43, Autonomous University of Madrid44, National Taiwan University45, Assumption University46, Boğaziçi University47, University College London48, University of Greenwich49
TL;DR: Leung et al. as mentioned in this paper revealed a five-dimensional structure of social axioms across individuals from five cultural groups across 41 nations and revealed the culture level factor structure and its correlates across 41 cultures.
Abstract: Leung and colleagues have revealed a five-dimensional structure of social axioms across individuals from five cultural groups. The present research was designed to reveal the culture level factor structure of social axioms and its correlates across 41 nations. An ecological factor analysis on the 60 items of the Social Axioms Survey extracted two factors: Dynamic Externality correlates with value measures tapping collectivism, hierarchy, and conservatism and with national indices indicative of lower social development. Societal Cynicism is less strongly and broadly correlated with previous values measures or other national indices and seems to define a novel cultural syndrome. Its national correlates suggest that it taps the cognitive component of a cultural constellation labeled maleficence, a cultural syndrome associated with a general mistrust of social systems and other people. Discussion focused on the meaning of these national level factors of beliefs and on their relationships with individual level factors of belief derived from the same data set.
443 citations
TL;DR: A quadratic time network algorithm is provided for computing an exact confidence interval for the common odds ratio in several 2×2 independent contingency tables, shown to be a considerable improvement on an existing algorithm developed by Thomas (1975), which relies on exhaustive enumeration.
Abstract: A quadratic time network algorithm is provided for computing an exact confidence interval for the common odds ratio in several 2×2 independent contingency tables. The algorithm is shown to be a considerable improvement on an existing algorithm developed by Thomas (1975), which relies on exhaustive enumeration. Problems that would formerly have consumed several CPU hours can now be solved in a few CPU seconds. The algorithm can easily handle sparse data sets where asymptotic results are suspect. The network approach, on which the algorithm is based, is also a powerful tool for exact statistical inference in other settings.
387 citations
TL;DR: Country-level factors that impact quantity and quality of online education include industry (business); governments at local, state, and federal levels; country laws; ICT capacity; Internet/mobile technology diffusion; and income and digital divide.
Abstract: Online education in its various modes has been growing steadily worldwide due to the confluence of new technologies, global adoption of the Internet, and intensifying demand for a workforce trained...
367 citations
TL;DR: In this article, a framework to understand the influence of community culture and family structure on divestment decisions in family firms is developed. But the authors focus on the varying levels of inertia to divest, depending on the values held by the owning family and the culture prevailing in their community.
Abstract: Timely acquisition and divestment of resources is essential for sustaining the competitive advantage and longevity of family firms. A combination of past successes, emotional attachments, and path dependencies can lead to extensive inertia toward divestment in these firms. This article develops a framework to understand the influence of community culture and family structure on divestment decisions in family firms. Propositions on the varying levels of inertia to divest—depending on the values held by the owning family and the culture prevailing in their community—are developed. Research and practical implications are discussed.
366 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 |