Areas of Expertise (10)
Music Industry
Business Intelligence
Online Communities
Information Diffusion
Data Analytics
Mobile App Strategy
Online Marketing
E-Business
Social Networks
Biography
Rajiv Garg is an assistant professor and an expert in the fields of information technology, e-commerce, data analytics, and economics. His work examines the influence of social networks and digital technologies on consumers and businesses. He has studied and lectured on the impact of LinkedIn and other social network connections on career advancement, and has uncovered data-driven insights regarding the music industry, software, mobile business, and consumer products.
Garg is an assistant professor of information, risk, and operation management at the McCombs School of Business, The University of Texas at Austin. He is a senior member of IEEE and has been serving on the board of various small corporations in the past decade.
Garg’s research work has appeared in the MIS Quarterly (MISQ), Journal of Management Information Systems (JMIS) and various peer reviewed conference proceedings.
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Education (5)
Carnegie Mellon University: Ph.D., Information Systems and Management 2013
Carnegie Mellon University: M.Phil., Public Policy and Management 2011
University of Southern California: M.Sc., Computer Science 2002
University of Southern California: M.Sc., Electrical Engineering 2001
Indian Institute of Technology (Banaras Hindu University), Varanasi: B.Tech., Electrical Engineering 2000
Media Appearances (5)
More Mergers After Dell-EMC? Maybe Not Best Option for Competitors
Xconomy online
2015-10-15
Rajiv Garg, an assistant professor at The University of Texas at Austin’s information, risk, and operations management department, discussed the deal and its potential fallout with Economy. Garg holds advanced degrees in information systems and management, computer science and electrical engineering, and has worked as a technology consultant and a project manager for Austin firm National Instruments (NASDAQ: NATI).
Dallas startup TerraTal plays matchmaker for job seekers, employers
The Dallas Morning News online
2015-08-21
LinkedIn’s system focuses on technical skills, eHarmony’s on personality traits, and TerraTal’s combines both, said Rajiv Garg, assistant professor of information management at the University of Texas at Austin.
Four Signs Your Employer Knows You're Looking to Leave
Fortune online
2014-10-27
Garg found that adding weak LinkedIn connections can actually reduce the number of job offers a person receives.
Looking for a Job? Having Too Many Contacts on LinkedIn May Backfire
UTNews online
2014-09-23
If your network is composed mostly of "weak ties" you may have increased access to job leads, but not to the referrals that turn leads into interviews and job offers.
Looking for a Job? Having Too Many Contacts on LinkedIn May Backfire
Know online
2014-09-22
The size and strength of your social network directly affects your ability to find new leads, get peer recommendations and land a job offer.
Sample Talks (1)
The Ties That Bind: Finding Jobs Through LinkedIn
Garg offers three key suggestions for building a professional LinkedIn network to improve a job search: 1) Identify: Use LinkedIn search functions to identify the people in your extended network who are linked to companies you’re interested in working for. 2) Connect: Maintain existing relationships with your close friends and colleagues. 3) Convert: Invest the time and effort to convert weak ties to strong ties and re-establish relationships with friends and former colleagues.
Style
Availability
- Keynote
- Workshop Leader
Articles (5)
Social Networks and Regional Advantages in Technology Entrepreneurship
SSRN
Research looks at both metro level characteristics such as funding rounds per year, and personal indicators such as regional social network density to create a model that explains the development of high tech regions around the globe.
To Be or Not to Be Linked: Online Social Networks and Job Search by Unemployed Workforce
Management Science
2018-08-01
In this paper, we first examine whether an individual’s social network plays a role in driving job search behavior, taking into account online social networking sites (e.g., LinkedIn) and other job search modes. Second, we examine how ties in online social networks affect job search outcomes (modeled sequentially as job leads, interviews, and offers), and we compare the findings to job outcomes from traditional job search modes (e.g., career fairs, newspaper, Internet postings, and friends and family).
Inferring App Demand from Publicly Available Data
MIS Quarterly
2013-12-01
In this research, we present an innovative method to use public data to infer the rank–demand relationship for the paid apps on Apple’s iTunes App Store.
Measuring Information Diffusion in an Online Community
Journal of Management Information Systems
2011-09-01
The goal of this paper is to develop an empirical approach for measuring information diffusion and discovery in online social networks that have these measurement challenges.
To Be Or Not To Be on LinkedIn: Job Search Using Online Social Networks
Social Science Research Network
2010-12-31
In this paper, we first examine if an individual’s social network still plays a role in driving his/her job search behavior not only on the social network but also on other modes.
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