Can Digital Skills Empower Disadvantaged Castes and Women? Evidence From India

Author:

Liu Che-Wei12,Saldanha Terence J.V.3ORCID,Mithas Sunil4ORCID

Affiliation:

1. Kelley School of Business, Indiana University, Bloomington, IN, USA

2. W. P. Carey School of Business, Arizona State University, Tempe, AZ USA

3. Terry College of Business, University of Georgia, Athens, GA, USA

4. Muma College of Business, University of South Florida, Tampa, FL, USA All authors contributed equally to the paper.

Abstract

How do digital skills influence individuals’ wages in contexts where caste-based and gender-based social stratification play an important role? We draw on sociology and economics literature to argue that the returns to digital skills in such contexts are shaped by caste and gender, and that digital skills empower disadvantaged individuals to increase their wages. Our empirical analysis of a rich micro-dataset on more than 20,000 individuals across all states in India from two waves of Indian Human Development Survey in 2005 and 2011 yields two key findings. First, we find that the positive returns to digital skills are greater for individuals from the Scheduled Castes and Scheduled Tribes in India than for individuals from other castes. Second, we find that the returns to digital skills are greater for women than for men. We also find that movement up the skilled occupation ladder is a mechanism that mediates the relationship between digital skills and wages. Our post hoc exploratory analyses suggest that among individuals from the lowest castes (Scheduled Castes and Scheduled Tribes), the returns to digital skills are greater for women than for men, and that returns to digital skills are lower in regions with less developed infrastructure and lower literacy rates than in other regions. We discuss the implications of our findings for diversity, equity, and inclusion research in operations management.

Publisher

SAGE Publications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3