Abstract
A Big Data maturity model (BDMM) is one of the key tools for Big Data assessment and monitoring, and a guideline for maximizing the usage and opportunity of Big Data in organizations. The development of a BDMM for SMEs is a new concept and is challenging in terms of development, application, and adoption. This article aims to create the novel online adaptive BDMM via responsive web application for SMEs. We develop the BDMM API and a responsive web application for easy access via mobile phone. We developed a model by analyzing the factors impacting the success of implementing Big Data Analytics (BDA) in SMEs based on literature reviews. The model was verified by conducting a survey of 180 SMEs in Thailand, interviewed against four extracted domains. Then, the scoring and classified levels for the model was developed through Latent Class Analysis (LCA) to depict four levels of each domain and four final maturity levels to create an adaptive model. As the experimental results with 33 users including executive officers, managers, IT and data analytic officers .The user acceptance for our mobile application using TAM indicates that executive officers group and non-executive group satisfied perceived usefulness, perceived ease of use, and intention to use factor. Use cases of the application include SMEs monitoring for their Big Data Analytics capability for improvement, and the Government Agency providing proper support on SMEs’ level of competency.
Highlights
Data are an extremely valuable asset in every business from large-scale enterprises to small and medium-sized enterprises (SMEs) and are considered the new oil [1]
The existing Big Data maturity model (BDMM) are ineffective for SME assessment, as the assessment could result in a low score and they cannot provide suggestions or recommendations for improvements in SMEs which is a guideline for using such a technology
We developed our BDMM as a mobile web application to create an easy-to-use, realtime, adaptive assessment tool to monitor the continuous improvement of organizations and gain the highest value of Big Data analytics (BDA) for SMEs
Summary
Data are an extremely valuable asset in every business from large-scale enterprises to small and medium-sized enterprises (SMEs) and are considered the new oil [1]. The term “Big Data” was initially defined in [2] to address the challenges of size, speed, and different formats of data that cannot be handled or processed by conventional methods. Since this term has been increasingly used in the fields of media, technology, and academics [3, 4]. SMEs are the lifeblood of Thailand and crucial for its economic growth They are defined by the number of employees and assets or revenue. Big Data maturity models (BDMMs) have been developed by multiple technology companies, researchers, and consulting firms. An adaptive model would more appropriate in the scenario
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
