Techknowledgey Transfer

Last registered on November 13, 2020


Trial Information

General Information

Techknowledgey Transfer
Initial registration date
November 13, 2020

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
November 13, 2020, 8:49 AM EST

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

Last updated
November 13, 2020, 8:53 AM EST

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


Primary Investigator

Kada Research

Other Primary Investigator(s)

PI Affiliation
Kada Research - Study Director

Additional Trial Information

On going
Start date
End date
Secondary IDs
The Techknowledgey Transfer project tests the concept of providing support to SMEs through student projects. Young people on a range of level 2 and 3 business, administration, enterprise and accountancy courses will work within SMEs to combine each young person's digital confidence, knowledge and understanding of the latest technologies with the SMEs to create and embed models of business and administration technology usage. Projects will be tailored to each business and be user-friendly and sustainable, and lead to improved business efficiencies, freeing up business owners and managers to increase productivity and profitability, as well as benefiting from an improved work-life balance.

The project was awarded to Petroc college through round 3 of the Business Basics programme. Business Basics aims to identify and test the most effective, scalable interventions that encourage SMEs to adopt existing technology and management practices and improve productivity. Business Basics is funded by the Department for Business, Energy and Industrial Strategy (BEIS), and administered by Innovate UK.
External Link(s)

Registration Citation

Dalgleish, Karl and Samuel Gillan. 2020. "Techknowledgey Transfer." AEA RCT Registry. November 13.
Experimental Details


Participating businesses will initially benefit from a 1:1 diagnostic session to identify areas where technology adoption could improve the efficiency and effectiveness of their business and administration processes. This will be followed by up to two masterclasses to learn about relevant technology options and network with peers in similar circumstances.
As this is a research trial, approximately half of all participating businesses will then be randomly selected to work with a student, who will embed the use of one or more identified technologies within their business and administration processes. Students will be selected on a competitive basis for each participating SME to ensure a good match between student and business, and both the student and business will be supported by expert tutors and/or business mentors.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1. Technology usage in key parts of the business
2. Technology adoption actions taken
3. Changes to business and administration activity (linked to technology adoption)
Primary Outcomes (explanation)
Measure one aims to investigate the adoption of specific technologies that can influence business and administration functions in an organisation. This outcome measure will determine the extent of technology use prior to (baseline survey) and after (final survey) receiving support.

Measure two investigates technology actions taken by the businesses after receiving the support.

Measure three aims to capture impacts on business and administration activity as a result of different intervention levels and consequent technology adoption. This measure will consist of two variables that attempt to understand the level of change to participant’s business activity (time and resource invested). To compare distance travelled we will ask questions in the baseline and final surveys.

Secondary Outcomes

Secondary Outcomes (end points)
1. Productivity related changes
2. Changes to business behaviours (linked to technology adoption)
3. Barriers
Secondary Outcomes (explanation)
1. This measure aims to capture specific productivity and commercial impacts as a result of technology adoption. Two measurement variables will be asked during the final survey, relating to changes to profitability and time/resource savings made, each as a direct result of the support/the technology adopted.

2. This measure aims to understand behavioural change linked to technology adoption through a series of questions that explores attitudes to new technology development and application of learning. They will be asked in both baseline and final survey depending on analysis metric.

3. This is designed to understand barriers that have been overcome as a result of support. A range of technology barriers will be listed, of relevance to the business cohort and. In baseline and final surveys we will provide a list of barriers for interviewees to confirm they do or do not face, exploring change from before receiving support and after.

Experimental Design

Experimental Design
Randomised Control Trial with parallel group design.
Experimental Design Details
This is an RCT with a parallel group design. The treatment group has two intervention arms: intervention level 1, the ‘Masterclass’ group, and intervention level 2, ‘Techknowledgey Transfer’. There will also be a counterfactual arm that experiences no intervention, used as an external control group for comparison against the treatment groups. As mentioned earlier, the counterfactual sample will be matched to the treatment group by an eligibility check/and firms with similar baseline characteristics.
The study is closer to a pragmatic trial than explanatory. Although certain eligibility criteria will be maintained, the trial will be conducted in a ‘real-life’ environment. It will feature a degree of flexibility and variation. For instance, students will have different characteristics and areas of study and the masterclasses and their trainers cover different aspects of technology. Also, the SMEs will vary by size, sector and maturity, and can potentially leave the trial if they choose.
Randomization Method
Microsoft Excel
Randomization Unit
Individual SME
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
Two arms with 100 SMEs each.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number


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