Recipient Organization
UNIV OF MINNESOTA
(N/A)
ST PAUL,MN 55108
Performing Department
Design, Housing & Apparel
Non Technical Summary
Big data analytics (BDA) is innovating the ways businesses draw insights from the ever-increasing amount of information available about consumer behavior. Big data represents the massive amount of structured and unstructured consumer interaction data which provides actionable descriptive and predictive insights. If captured and analyzed properly, big data has the potential to help businesses achieve efficiency, reduce fraud, increase sales, enhance customer service, and lower operation costs (Olufemi, 2019).Despite these benefits, the adoption and use of BDA have been mainly restricted to large and multi-national companies due to the significant investment involved (Baldwin, 2015). Small businesses, which hire fewer than 500 employees, are lagging behind in the usage of big data analytics since they often lack trained specialists with analytic expertise and face cultural and financial barriers within the organization (Coleman et al., 2016). In Minnesota, small businesses are the backbone of the state's economy, as they represent over 94% of the total businesses in Minnesota and are responsible for 52% of job creation (Bodin, 2017). Recently, small businesses were hit especially hard by the COVID-19 pandemic, thus there is a critical need for small businesses to meet the changing consumer behavior and industry trends through big data.This proposal seeks to understand the utilization and application of BDA among small-sized businesses in Minnesota in a comprehensive manner. Specifically, the first stage will involve examining barriers to big data analytics adoption (e.g., organizational culture, resources) through a survey of Minnesota small businesses. The second stage will entail developing case studies that describe successful implementation of BDA and how it helped businesses remain resilient during the pandemic. The final stage involves developing a comprehensive framework for the successful implementation of BDA in small businesses. Such framework will help small businesses in Minnesota cultivate big data capability and excel in their growth post-pandemic. The findings of the study will be shared among business owners who participate in the study and academics for wider dissemination.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Big data analytics (BDA) is innovating the ways businesses draw insights from the ever-increasing amount of information available about consumer behavior. Big data represents the massive amount of structured and unstructured consumer interaction data which provides actionable descriptive and predictive insights. If captured and analyzed properly, big data has the potential to help businesses achieve efficiency, reduce fraud, increase sales, enhance customer service, and lower operation costs (Olufemi, 2019).Despite these benefits, the adoption and use of BDA have been mainly restricted to large and multi-national companies due to the significant investment involved (Baldwin, 2015). Small businesses, which hire fewer than 500 employees, are lagging behind in the usage of big data analytics since they often lack trained specialists with analytic expertise and face cultural and financial barriers within the organization (Coleman et al., 2016). In Minnesota, small businesses are the backbone of the state's economy, as they represent over 94% of the total businesses in Minnesota and are responsible for 52% of job creation (Bodin, 2017). Recently, small businesses were hit especially hard by the COVID-19 pandemic, thus there is a critical need for small businesses to meet the changing consumer behavior and industry trends through big data.This proposal seeks to understand the utilization and application of BDA among small businesses in Minnesota in a comprehensive manner and suggests BDA implementation methods for enhanced firm performance. A total of three objectives and outcomes are explained below. The outcome of each phase will be developed into manuscripts and submitted to conferences (e.g., Academy of Marketing Science) and academic journals (e.g., Journal of Small Business Management, International Journal of Entrepreneurship and Small Business) for dissemination.Phase 1. To figure out how small businesses can implement BDA to improve performances, the first question to ask is "what has prevented small businesses from adopting BDA thus far?" Thus, the first stage of this project will involve examining the barriers to BDA adoption (such as organizational culture and resources) through a survey of the small businesses in Minnesota. The current status of BDA adoption (such as types of BDA use, length of BDA use, and BDA's significance in operation) will also be assessed at this stage. Drawing from the theories of resource-based view and diffusion of innovation, hypotheses may include the following:Lack of tangible resources (such as personnel, financial support, state resources) decreases a firm's capacity to innovateLack of intangible resources (such as understanding of BDA, organizational culture, management support) decreases a firm's capacity to innovateThe moderating role of the COVID-19 pandemic (i.e., slowing the adoption of BDA)Phase 2. Upon surveying small businesses, several firms with notable BDA implementation strategies and applications will be selected and developed into case studies. These case studies will feature how small enterprises have utilized BDA to meet the changing consumer demands and weather the pandemic. The research questions to be answered include the following:How did the small businesses effectively implement BDA as part of their operation?What are the key benefits of BDA in operation, customer management, and branding?In what ways did BDA help the small businesses to remain resilient to the consumer and industry shift caused by the pandemic?Phase 3. The third objective is to develop a comprehensive framework for implementing BDA among small businesses based on previous findings (stage 1 and 2). The benefits, challenges, and opportunities of BDA implementation for small businesses will be identified and tested through a large-scale online survey. The outcome of this stage will provide meaningful implications for academics and small businesses on how to innovate using BDA.
Project Methods
Phase 1. Current Status and Barriers to BDA AdoptionResearch Method/Data Collection: Online survey of key decision-makers (e.g., CEO, founder, managers, directors) of Minnesota small businessesTarget Number of Respondents: 100-150Timeline: 7 - 8 monthsLocation/Facility: Online data collection; data will be analyzed via PI's software & computerPhase 2. Models of Successful BDA ImplementationResearch Method/Data Collection: In-depth interviews via zoom with key decision-makers (e.g., CEO, founder, managers, directors) of Minnesota small businessesTarget Number of Respondents: 5-8Timeline: 5 - 6 monthsLocation/Facility: Online data collection; data will be analyzed via PI's software & computerPhase 3. Development of a Conceptual Framework for BDA ImplementationResearch Method/Data Collection: Online survey of key decision-makers (e.g., CEO, founder, managers, directors) of Minnesota small businessesTarget Number of Respondents: 100-150Timeline: 7 - 8 monthsLocation/Facility: Online data collection; data will be analyzed via PI's software & computer