Data analytics offers a wide variety of opportunities across all industries enabling improvements in all business operations. Data analytics adoption has several associated complexities making it cumbersome and challenging for organizations. In particular, small and medium businesses (SMB) and nonprofit organizations lag behind data analytics adoption, even though they are crucial for the economy and would benefit most from data-driven decisions. This paper aims to identify factors that influence data analytics adoption by organizations. We conduct a systematic literature review to identify articles relevant to data analytics adoption studies performed using survey methodology. We synthesize literature review results to propose a research model to investigate data analytics adoption in small & medium businesses and nonprofit organizations. The proposed research model was developed primarily based on Technology Organization Environment (TOE) framework, combined with other factors relevant to data analytics adoption found in the literature. The research model investigates the influences of data analytics, organization, and environment characteristics on data analytics adoption by SMBs and nonprofits. We hope that further progress with this research will provide insights into helping SMBs and nonprofits adopt data analytics technologies.

1. Systematic Literature Review
and Research Model to Examine
Data Analytics Adoption in
Organizational Contexts
ARIELLE O’NEAL
M.S. Data Science
KARTHIKEYAN UMAPATHY
(Presenter)
Co-Director of Florida Data Science for Social Good
Associate Professor
School of Computing
University of North Florida
Jacksonville, FL
University of North Florida
Jacksonville, FL

2. Data-Driven Culture
 Development ofWeb and Mobile application systems has helped organizations gather
data on every aspect of our life
 Social activities, science, work, health, and infrastructure
 As we transform into a data-centric economy, becoming a data-driven organization is
fundamental for survival
 Organizations are seeking to infuse data-driven culture
 Data-driven culture can be interpreted as a process involving data collection, data
analysis, model building, gaining actional insights, converting insights into business
value & competitive edge.
Organizations are trying to stay on cutting edge of competition as many large
organizations have already adopted capability to implement data analytics tools

3. Research Focus: Data Analytics Adoption
 Data analytics tools allow businesses to identify and predict trends and keep up with
supply and demand
 Access to the tools and talents are not universally accessible to all organizations
 McKinsey Analytics and NewVantage Partners have investigated data analytics adoption
by large organizations
 While facing considerable challenges, large organizations are ramping up investments to adopt data
analytic tools
 Small & Medium business and non-profit organizations have not been thoroughly
studied in the context of data analytics adoption
 Addressing this gap is the key research focus

4. Systematic Literature Review of Data Analytics Adoption
Studies: Data Collection
 Google Scholar was chosen as key scientific database for data collection
The keywords used in the search were a combination of “data analytics adoption”,
“business analytics adoption”, “data science adoption”, “survey method”, and
“benchmark” to identify relevant articles
The search was restricted to articles published from 2010 to 2022
 As the data analytics topic emerged in the late 2000s and early 2010s
The base inclusion criteria consisted of articles that were free to access, written in
English, and published through a peer-review process.
 Articles that were journals, conference proceedings, workshop papers, and book
chapters were considered. Articles that were unrelated to data analytics adoption or their
full texts were not available were excluded.

5. Data Extraction
We extracted data on article title,
first author affiliation location,
research method, study focus,
whether survey questions were
included, theoretical framework,
statistical analysis, and
organization focus
 Data were extracted and documented
using Microsoft Excel files

6. Findings of Systematic
Literature Review of Data
Analytics Adoption Studies

7. Methodology of Studies Identified
0 2 4 6 8 10 12
Quantative survey method
Interview and case study
Mixed method - survey and case study

8. Survey Method
0 1 2 3 4 5 6 7 8 9
5-point
7-point
Did not specify
Likert Scales  Of the 11 studies, 9 used survey
instruments for gathering data
on data analytics adoption in the
published article

9. Theoretical Framework
Technology Acceptance Model (TAM)
 Motivation Model (MM)
 Diffusion of Innovations (DOI)
 UnifiedTheory ofAcceptance and Use ofTechnology (UTAUT)
 Technology Organization Environment (TOE) – 5 out of 13
 Resourced-based
Situation Complication Question and Answer (SCQA)
 ComplexityTheory
 InstitutionalTheory

10. Analysis Performed
 Quantitative Analysis
 7 studies used Partial Least Squares (PLS) or PLS Structural Equation Model (PLS-SEM)
 Factor analysis
 Regression
 Neural networks
 Qualitative Analysis
 Thematic analysis

11. Organization Size and Industry Sector
 Many studies were not focused on the business size
Various organization sizes were most frequent in the selected review studies
 3 studies focused on Small & Medium Enterprises, one study focused on medium and
large organizations
 Most studies were not focused on particular industry sector
 Manufacturing – 2 studies
 Construction
 Healthcare
 Retail
 Governance services

12. Country of Study
Country Frequency
Malaysia 3
India 2
Pakistan 1
Taiwan 1
France 1
Greece 1
Spain 1
United Kingdom 1
Colombia 1
Cameroon 1
Asia, 7
Europe, 4
Africa, 1
South America, 1
Count
The lack of studies on
North American countries
is a research gap that must
be addressed.

13. Research Focus of Studies Observed  Factors studied:
 Firm performance
 COVID-19 crisis
 Organizational context
 Strategic determinants
 Continual usage
 Process innovation
 Predicting adoption
Technology readiness
 Project management
 Sustainability
Transformational leadership
Data Analytics Focus Frequency
Big data 9
Business analytics 2
Social media 1
Technology implementation 1

14. Data Analytics Adoption: Small
& Medium Businesses vs.
Nonprofits

15. Proposed Research Model
The purpose of this
study is to
inductively develop
a research model
for data analytics
adoption for SMBs
and nonprofit
organizational
contexts through
articles found using
the systematic
literature review

16. Research Plan
 Create survey instrument that will be used for benchmarking data analytics adoption by
SMBs and nonprofits
 SMB and nonprofit subject matter experts would be contacted for validating survey
instrument
 After obtaining IRB permits, survey will be distributed to SMBs registered with
Jacksonville Chamber and nonprofits registered with Nonprofit Center for Northeast
Florida
 The survey data collection would be conducted for three months
 Descriptive and confirmatory factor analysis would be performed on survey responses
from SMBs and nonprofits

17. Karthikeyan Umapathy
k.umapathy@unf.edu
Any Questions