Digital media analytics  gathers qualitative and quantitative data from social media websites and analyzes that data using social media analytics tools to facilitate business decisions. Used largely to mine customer behaviour for support marketing and customer service activities, it measures the performance of digital properties and extracts the information in such a way that actionable insights can be deduced from the analysis. To understand the contribution of digital media better, we aim to analyze an organization’s varied requirement and specific contribution of business analytics to a firm’s performance.
Managers who use AI will replace who don’t

Managers Who Use AI Will Replace Those Who Don’t 

Artificial Intelligence and Automation
Emergent research posits that artificial intelligence (AI), especially machine intelligence (MI), is the most important general-purpose technology of our era. Rapid advances in MI are engendering economically significant applications in speech and face recognition, customer retention, R&D, trading, anomaly detection, and operations and workflow design, amongst others, across diverse sectors. These applications, in turn, are giving rise to new tasks and occupations, new processes, and new business models, whose contribution is expected to increase from $1.3 billion in 2016 to $59 billion in 20251. However, the evidence of such impact is generally anecdotal in that it has largely comprised a relatively small number of use cases that are not generalizable to a larger cohort of firms and industries. 

SRITNE is interested in studying AI-based workflow automation and work models based on empirical data to present statistical evidence of the systematic and increasingly pervasive impacts of AI on business and society. 
Work From Home Survey
Over the past decade, organizations have increasingly embraced diverse distributed and remote work arrangements. However, the implications of these arrangements have been under-investigated since they are not systematic or pervasive - they have typically been limited to a select group of occupations and organizations. All of that seems to be fast changing with the outbreak of COVID-19. Several millions of workers across diverse sectors and organizational types have been asked to self-quarantine and/ or work from home. In this context, it is valuable, necessary even, to understand the impact of such arrangements on workers, organizations, and society.
To understand these issues better, we have rolled out a brief online survey about the impact of sudden remote work on staff and organizations. We hope to observe how coping strategies of firms evolve in the short run.
The results will inform organizational prescriptions to deal with such challenges and also, provide policy makers with more information to guide such arrangements, including design effective risk mitigation strategies and minimize disruptions.
Our survey complements independent analyses and development of a Work From Home (WFH) index that assesses the amenability of various jobs to remote working. We will publish findings from the survey analyses as well as the WFH index
The Economic Impacts of Private Ridesharing: Quality of Urban Mobility and Labour Market Effects
Research Partner: Niti Aayog

Cities around the world, especially in developing countries, are grappling with the problem of traffic congestion. A recent study by the Centre for Science and Environment (CSE) reports that Delhi experiences almost twelve hours of ‘peak  hour  traffic’.  Congestion adversely impacts economic activity and worker productivity, air pollution, and fuel costs, rendering it a major scourge of cities worldwide. That  ridesharing  platforms  reduce  congestion  and  improve  quality  of  urban  mobility assumes  that these  platforms  substitute private  car  ownership to  reduce  each  individual’s vehicle  miles  travelled  (VMT)  and  congestion.  However, ridesharing platforms might draw  commuters  from  public  transport and  other high  occupancy shared  mobility  services, thereby,  increasing  VMT  and  congestion. App-based taxi services have proliferated at a rapid pace, yet their impact on the quality of urban mobility remains unclear. Ridesharing services have a theoretically ambiguous impact on mobility: On the one hand, they may reduce private car ownership, improve utilisation, while on the other hand, they may draw commuters from public transport into using these more convenient modes of transport.
 
To address this lack of  empirical  evidence  on  the  impacts  of ridesharing  platforms  we use  an  exogenous  disruption  of  ridesharing  services  in Delhi to causally estimate the impact of ridesharing platforms on congestion. Our analyses of impact  are informed  by granular  route-level  traffic  data  collected  from  Google  Maps  and complementary ridership  data  from  the  Delhi  Metro  Rail  Corporation  (DMRC)  and  other transport services.