SBIR Program Supporting Statement B

National Institute of Food and Agriculture

U.S. Department of Agriculture

OMB No. 0524-XXXX

Small Business Innovation Research (SBIR) Phase III Commercialization Survey

SUBJECT: Supporting Statement B. Small Business Innovation Research (SBIR) Program to Implement a Phase III Commercialization Survey

B. Statistical Methods

1. Respondent Universe and Sampling Methods

(Describe (including a numerical estimate) the potential respondent universe and any sampling or other respondent selection method to be used. Data on the number of entities (e.g., establishments, State and local government units, households, or persons) in the universe covered by the collection and in the corresponding sample are to be provided in tabular form for the universe as a whole and for each of the strata in the proposed sample. Indicate expected response rates for the collection as a whole. If the collection had been conducted previously, include the actual response rate during the last collection.)

SBIR Phase II Survey. The universe of participants includes small business owners who received Phase III SBIR grant awards from the National Institute of Food and Agriculture (NIFA) between 1994 and 2014. Surveys will be sent to all participants so sampling will not be involved. Results will not be used to make statements representative of all SBIR Phase II awardees and are not intended to be generalizable beyond the respondent group.

Number in Universe	Entity
n=500	Small business owners

This will be the first survey of its kind for the agency. However, we estimate that we can achieve at least a 30% response rate based on previous relationships with our past SBIR Phase III awardees.

Data collection of this type has not been done previously; there is no precedent to predict specific response rates.

2. INFORMATION COLLECTION PROCEDURES

(Describe the procedures for the collection of information including:

1. Statistical methodology for stratification and sample selection;

2. Estimation procedure;

3. Degree of accuracy needed for the purpose described in the justification;

4. Unusual problems requiring specialized sampling procedures; and,

5. Any use of periodic (less frequent than annual) data collection cycles to reduce burden.)

No estimation or stratification is used because we will survey 100% of the SBIR participant population. Participant information will be pulled from an internal database at the agency. Specifically, we began with a universe of approximately 700 businesses. The agency conducted an analysis to determine which businesses were still viable (via Internet searches), resulting in a list of 500 businesses estimated as potential respondents.

Upon OMB approval, NIFA will contract with an organization (via competitive procurement) to:

1. build the Internet-based survey;

2. announce and solicit survey responses via mass e-mail announcements;

3. collect and store the data in a secure database; and

4. analyze the data and report it to the NIFA Project Officer

Additionally, because the survey contains proprietary information, NIFA will add terms and conditions to the contract to ensure that confidentiality is maintained throughout each data collection point.

Data collection will occur as follows:

	T1. Baseline	T2. First Follow-up
Begins…	Upon OMB clearance and contractor award.	3 years after baseline
Sent to…	n=500 small business owners	n=500 small business owners
Via…	E-mail containing a link to the survey	E-mail containing a link to the survey
First E-mail Reminder Sent…	2 weeks after the initial e-mail	2 weeks after the initial e-mail
Second E-mail Reminder Sent…	2 weeks after the first reminder	2 weeks after the first reminder
Final Reminder	2 weeks after the second reminder as direct contact via phone call	2 weeks after the second reminder as direct contact via phone call

We estimate that a 30% response rate (e.g., 150 businesses) at each data collection point should provide a reasonable number of business owners to assess the success of commercialization funded by NIFA.

3. METHODS TO MAXIMIZE RESPONSE RATES

(Describe methods to maximize response rates and to deal with issues of non-response. The accuracy and reliability of information collected must be shown to be adequate for intended uses. For collections based on sampling, a special justification must be provided for any collection that will not yield “reliable” data that can be generalized to the universe studied.)

As stated above, the contractor will employ mass e-mail marketing techniques to highlight the importance of participation in the survey. Further, many of the past awardees have prior working relationships with NIFA staff who will promote participation in the survey at SBIR conferences and meetings.

3. TESTS OF PROCEDURES

(Describe any tests of procedures or methods to be undertaken. Testing is encouraged as an effective means of refining collections of information to minimize burden and improve utility. Tests must be approved if they call for answers to identical questions from 10 or more respondents. A proposed test or set of tests may be submitted for approval separately or in combination with the main collection of information.)

The survey was developed by Larta, Inc., who used data elements from the Small Business Administration (SBA) commercialization matrix. This is important to note because the matrix was vetted and tested by several industry leaders and valid and representative.

Further, Larta pretested the proposed instrument with several companies for timing, clarity, and feasibility. Feedback was used to craft the attached survey.

3. STATISTICAL CONSULTANTS

(Provide the name and telephone number of individual consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.)

NIFA did not consult with any outside individual on the statistical aspects of the design of its survey. NIFA employees who will collect and/or analyze the information are:

Scott Dockum at NIFA will be the Project Officer of the contract responsible for the data collection and analysis.

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