The Role of Digital Knowledge Management Tools in Emerging Marketplaces: Evidence from an Intervention in West Bengal, India

Last registered on February 28, 2022


Trial Information

General Information

The Role of Digital Knowledge Management Tools in Emerging Marketplaces: Evidence from an Intervention in West Bengal, India
Initial registration date
May 28, 2021

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
May 28, 2021, 4:08 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
February 28, 2022, 2:20 PM EST

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
Indian Institute of Management, Calcutta
PI Affiliation
Indian Institute of Management, Calcutta

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Rural entrepreneurs in India commonly suffer from access gaps that prevent linkage to larger metropolitan area opportunities. These access gaps exist despite the recent proliferation of mobile internet infrastructure. Bridging these gaps therefore requires tools that go beyond the simple availability of resources, and are affordable/self-sustaining. To this end, our objective is to demonstrate how current internet-based social technologies can be used to build a social knowledge management framework. We posit that this framework will enhance the knowledge capability of rural entrepreneurs, which in turn will positively affect entrepreneurial competency and performance. Our intervention is targeted towards artisans in Birbhum, West Bengal, and will involve enhancing digital literacy along several axes with hands on training as well as asynchronous material shared via Whatsapp-based communities. In a pre-intervention pilot study, we are able to successfully form active Whatsapp communities with a group of artisans and onboard them to use a digital storefront ( Using survey instruments on this pilot sample, we first develop reliable scales for measuring the key constructs. Next, we see that knowledge capability strongly correlates with entrepreneurial competency, which in turn correlates with performance. This suggests that any intervention targeted at enhancing capabilities can have positive trickle down effects. Our intervention is now being deployed in the field as a 50-week stepped-wedge RCT for impact assessment. As “social intermediaries”, we aim to facilitate re-tooling and community building, both of which can be self-sustaining and have the potential to bring concrete socio-economic benefits even after the intervention. In general, our findings can have large scale policy implications for bottom of pyramid (BOP) entrepreneurs by identifying mechanisms through which digital knowledge management tools can lead to greater entrepreneurial success in emerging markets.
External Link(s)

Registration Citation

Banerjee, Shrabastee, Somprakash Bandyopadhyay and Sneha Bhattacharyya. 2022. "The Role of Digital Knowledge Management Tools in Emerging Marketplaces: Evidence from an Intervention in West Bengal, India." AEA RCT Registry. February 28.
Experimental Details


The objective of this project is to demonstrate how the current internet-based social technologies has the potential of building business knowledge capabilities and enhancing the entrepreneurial competencies of rural artisans by bridging rural-urban knowledge & information divide through the creation of a social knowledge management framework. The project ultimately aims at creating rural business transformation using social technologies with the potential to eradicate sharp economic, social, and cultural difference between rural and urban producers. We will run a 50 week field study to measure medium to long term impacts of our intervention.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
E-readiness, technological capability, technology adoption propensity, knowledge capability, entrepreneurial competency and entrepreneurial performance.
Primary Outcomes (explanation)
Based on a pilot sample of 50 artisans, we have developed survey scales (each with a set of 8 to 12 questions measured on a 1-5 Likert scale) for each of these outcomes. We also have 3 open ended numeric performance questions (number of order inquiries, number of ongoing orders, total amount earned from these orders) collected based on recall.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will deploy a cluster randomized trial, with clusters being defined based on locations in Birbhum, West Bengal. Given logistical constraints, our intervention can only be deployed to one cluster at a time. Hence, we will use a stepped-wedge cluster randomized trial (SW-CRT), which involves the sequential transition of clusters from control to intervention conditions in randomized order, until all clusters are exposed.

Experimental Design Details
During the 50-week study period, participating groups of artisans (40 groups in total, with roughly 15 participants in each) will cross over from control to intervention phase (i.e, one-way switch over) in different weeks throughout the year. The timing of crossover is randomised across locations, with each of the 40 groups belonging to a specific area of Birbhum, West Bengal. Measurements will be solicited once every 10 weeks to track outcomes over time. Finally, for a subset of early participants, follow-up measures will be sought 10-20 weeks after the study period.
Randomization Method
Using random number generator on R
Randomization Unit
Locations/pincodes in Birbhum, West Bengal.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
The design is a stepped wedge cluster-randomised trial, so all units are eventually treated.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Mean difference: 0.245 Standard deviation: 1 Significance level: 0.05 Number clusters per sequence: 10 WP-ICC: 0.3 WP-ICC (lower): 0.1 WP-ICC (upper): 0.6 CAC: 0.8 Individual auto-correlation: 0.8 80% power to detect a mean shift of 6-7%.

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials